Upload folder using huggingface_hub

adapter_config.json

@@ -0,0 +1,38 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "llava-hf/llava-v1.6-mistral-7b-hf",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": [
+    14,
+    15,
+    16
+  ],
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "q_proj",
+    "k_proj",
+    "gate_proj",
+    "down_proj",
+    "up_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fff09724160dcf4cf64f0f6eb34e5721245c37d345a0397afa63ea29ef656359
+size 8463296

added_tokens.json

@@ -0,0 +1,4 @@
+{
+  "<image>": 32000,
+  "<pad>": 32001
+}

chat_template.json

@@ -0,0 +1,3 @@
+{
+  "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{ '<<SYS>>\n' + message['content'][0]['text'] + '\n<</SYS>>\n\n' }}{% elif message['role'] == 'user' %}{{ '[INST] ' }}{# Render all images first #}{% for content in message['content'] | selectattr('type', 'equalto', 'image') %}{{ '<image>\n' }}{% endfor %}{# Render all text next #}{% for content in message['content'] | selectattr('type', 'equalto', 'text') %}{{ content['text'] }}{% endfor %}{{' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + message['content'][0]['text'] + '<\\s> '}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}"
+}

checkpoint-150/README.md

@@ -0,0 +1,202 @@
+---
+base_model: llava-hf/llava-v1.6-mistral-7b-hf
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.2

checkpoint-150/adapter_config.json

@@ -0,0 +1,38 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "llava-hf/llava-v1.6-mistral-7b-hf",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": [
+    14,
+    15,
+    16
+  ],
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "q_proj",
+    "k_proj",
+    "gate_proj",
+    "down_proj",
+    "up_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

checkpoint-150/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fff09724160dcf4cf64f0f6eb34e5721245c37d345a0397afa63ea29ef656359
+size 8463296

checkpoint-150/added_tokens.json

@@ -0,0 +1,4 @@
+{
+  "<image>": 32000,
+  "<pad>": 32001
+}

checkpoint-150/global_step150/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:33992f71b8ea90c3f5cfd267a2f625331da9e5fd80e8d7717bd0605209880fee
+size 50735920

checkpoint-150/global_step150/mp_rank_00_model_states.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:44d38c911bfdfd7c9affdd57852004c18e58c6879b7edf4f2c0468d5f13bd68e
+size 8572972

checkpoint-150/latest

@@ -0,0 +1 @@
+global_step150

checkpoint-150/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5edd7f3ff6a59dc0a2b336b5a3ee54fd3c5109f037c294f92c82c3c440b2aa98
+size 14244

checkpoint-150/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8e798919863d5686f94541bc841a519bc9110a8f1214e3a80d4ecfaac070dc79
+size 1000

checkpoint-150/special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "</s>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

checkpoint-150/tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
+size 493443

checkpoint-150/tokenizer_config.json

@@ -0,0 +1,69 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32000": {
+      "content": "<image>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32001": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "extra_special_tokens": {
+    "image_token": "<image>"
+  },
+  "image_token": "<image>",
+  "legacy": true,
+  "max_length": null,
+  "model_max_length": 8192,
+  "pad_to_multiple_of": null,
+  "pad_token": "</s>",
+  "pad_token_type_id": 0,
+  "padding_side": "left",
+  "processor_class": "LlavaNextProcessor",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

checkpoint-150/trainer_state.json

@@ -0,0 +1,138 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.24,
+  "eval_steps": 1000.0,
+  "global_step": 150,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.016,
+      "grad_norm": 0.05375732481479645,
+      "learning_rate": 0.0001,
+      "loss": 4.9168,
+      "step": 10
+    },
+    {
+      "epoch": 0.032,
+      "grad_norm": 0.06290680170059204,
+      "learning_rate": 0.0001,
+      "loss": 4.7727,
+      "step": 20
+    },
+    {
+      "epoch": 0.048,
+      "grad_norm": 0.18232201039791107,
+      "learning_rate": 0.0001,
+      "loss": 4.6199,
+      "step": 30
+    },
+    {
+      "epoch": 0.064,
+      "grad_norm": 4.475333213806152,
+      "learning_rate": 0.0001,
+      "loss": 4.2628,
+      "step": 40
+    },
+    {
+      "epoch": 0.08,
+      "grad_norm": 5.602807998657227,
+      "learning_rate": 0.0001,
+      "loss": 2.2105,
+      "step": 50
+    },
+    {
+      "epoch": 0.096,
+      "grad_norm": 4.922974586486816,
+      "learning_rate": 0.0001,
+      "loss": 1.4091,
+      "step": 60
+    },
+    {
+      "epoch": 0.112,
+      "grad_norm": 7.1347479820251465,
+      "learning_rate": 0.0001,
+      "loss": 0.85,
+      "step": 70
+    },
+    {
+      "epoch": 0.128,
+      "grad_norm": 3.1461501121520996,
+      "learning_rate": 0.0001,
+      "loss": 0.6901,
+      "step": 80
+    },
+    {
+      "epoch": 0.144,
+      "grad_norm": 1.2969322204589844,
+      "learning_rate": 0.0001,
+      "loss": 0.5742,
+      "step": 90
+    },
+    {
+      "epoch": 0.16,
+      "grad_norm": 2.384674549102783,
+      "learning_rate": 0.0001,
+      "loss": 0.781,
+      "step": 100
+    },
+    {
+      "epoch": 0.176,
+      "grad_norm": 1.1518051624298096,
+      "learning_rate": 0.0001,
+      "loss": 0.6573,
+      "step": 110
+    },
+    {
+      "epoch": 0.192,
+      "grad_norm": 1.042501449584961,
+      "learning_rate": 0.0001,
+      "loss": 0.7151,
+      "step": 120
+    },
+    {
+      "epoch": 0.208,
+      "grad_norm": 2.2350070476531982,
+      "learning_rate": 0.0001,
+      "loss": 0.6271,
+      "step": 130
+    },
+    {
+      "epoch": 0.224,
+      "grad_norm": 29.857282638549805,
+      "learning_rate": 0.0001,
+      "loss": 1.2141,
+      "step": 140
+    },
+    {
+      "epoch": 0.24,
+      "grad_norm": 1.7340813875198364,
+      "learning_rate": 0.0001,
+      "loss": 0.8102,
+      "step": 150
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 150,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 1,
+  "save_steps": 500,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": true
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 5.484662633791488e+16,
+  "train_batch_size": 8,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-150/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b687191320ebcf3b23eba17022227dbbdb99144f49afde09c51ab32e4eacc1f2
+size 6840

checkpoint-150/zero_to_fp32.py

@@ -0,0 +1,674 @@
+#!/usr/bin/env python
+
+# Copyright (c) Microsoft Corporation.
+# SPDX-License-Identifier: Apache-2.0
+
+# DeepSpeed Team
+
+# This script extracts fp32 consolidated weights from a zero 1, 2 and 3 DeepSpeed checkpoints. It gets
+# copied into the top level checkpoint dir, so the user can easily do the conversion at any point in
+# the future. Once extracted, the weights don't require DeepSpeed and can be used in any
+# application.
+#
+# example:
+#   python zero_to_fp32.py . output_dir/
+#   or
+#   python zero_to_fp32.py . output_dir/ --safe_serialization
+
+import argparse
+import torch
+import glob
+import math
+import os
+import re
+import json
+from tqdm import tqdm
+from collections import OrderedDict
+from dataclasses import dataclass
+
+# while this script doesn't use deepspeed to recover data, since the checkpoints are pickled with
+# DeepSpeed data structures it has to be available in the current python environment.
+from deepspeed.utils import logger
+from deepspeed.checkpoint.constants import (DS_VERSION, OPTIMIZER_STATE_DICT, SINGLE_PARTITION_OF_FP32_GROUPS,
+                                            FP32_FLAT_GROUPS, ZERO_STAGE, PARTITION_COUNT, PARAM_SHAPES, BUFFER_NAMES,
+                                            FROZEN_PARAM_SHAPES, FROZEN_PARAM_FRAGMENTS)
+
+
+@dataclass
+class zero_model_state:
+    buffers: dict()
+    param_shapes: dict()
+    shared_params: list
+    ds_version: int
+    frozen_param_shapes: dict()
+    frozen_param_fragments: dict()
+
+
+debug = 0
+
+# load to cpu
+device = torch.device('cpu')
+
+
+def atoi(text):
+    return int(text) if text.isdigit() else text
+
+
+def natural_keys(text):
+    '''
+    alist.sort(key=natural_keys) sorts in human order
+    http://nedbatchelder.com/blog/200712/human_sorting.html
+    (See Toothy's implementation in the comments)
+    '''
+    return [atoi(c) for c in re.split(r'(\d+)', text)]
+
+
+def get_model_state_file(checkpoint_dir, zero_stage):
+    if not os.path.isdir(checkpoint_dir):
+        raise FileNotFoundError(f"Directory '{checkpoint_dir}' doesn't exist")
+
+    # there should be only one file
+    if zero_stage <= 2:
+        file = os.path.join(checkpoint_dir, "mp_rank_00_model_states.pt")
+    elif zero_stage == 3:
+        file = os.path.join(checkpoint_dir, "zero_pp_rank_0_mp_rank_00_model_states.pt")
+
+    if not os.path.exists(file):
+        raise FileNotFoundError(f"can't find model states file at '{file}'")
+
+    return file
+
+
+def get_checkpoint_files(checkpoint_dir, glob_pattern):
+    # XXX: need to test that this simple glob rule works for multi-node setup too
+    ckpt_files = sorted(glob.glob(os.path.join(checkpoint_dir, glob_pattern)), key=natural_keys)
+
+    if len(ckpt_files) == 0:
+        raise FileNotFoundError(f"can't find {glob_pattern} files in directory '{checkpoint_dir}'")
+
+    return ckpt_files
+
+
+def get_optim_files(checkpoint_dir):
+    return get_checkpoint_files(checkpoint_dir, "*_optim_states.pt")
+
+
+def get_model_state_files(checkpoint_dir):
+    return get_checkpoint_files(checkpoint_dir, "*_model_states.pt")
+
+
+def parse_model_states(files):
+    zero_model_states = []
+    for file in files:
+        state_dict = torch.load(file, map_location=device)
+
+        if BUFFER_NAMES not in state_dict:
+            raise ValueError(f"{file} is not a model state checkpoint")
+        buffer_names = state_dict[BUFFER_NAMES]
+        if debug:
+            print("Found buffers:", buffer_names)
+
+        # recover just the buffers while restoring them to fp32 if they were saved in fp16
+        buffers = {k: v.float() for k, v in state_dict["module"].items() if k in buffer_names}
+        param_shapes = state_dict[PARAM_SHAPES]
+
+        # collect parameters that are included in param_shapes
+        param_names = []
+        for s in param_shapes:
+            for name in s.keys():
+                param_names.append(name)
+
+        # update with frozen parameters
+        frozen_param_shapes = state_dict.get(FROZEN_PARAM_SHAPES, None)
+        if frozen_param_shapes is not None:
+            if debug:
+                print(f"Found frozen_param_shapes: {frozen_param_shapes}")
+            param_names += list(frozen_param_shapes.keys())
+
+        # handle shared params
+        shared_params = [[k, v] for k, v in state_dict["shared_params"].items()]
+
+        ds_version = state_dict.get(DS_VERSION, None)
+
+        frozen_param_fragments = state_dict.get(FROZEN_PARAM_FRAGMENTS, None)
+
+        z_model_state = zero_model_state(buffers=buffers,
+                                         param_shapes=param_shapes,
+                                         shared_params=shared_params,
+                                         ds_version=ds_version,
+                                         frozen_param_shapes=frozen_param_shapes,
+                                         frozen_param_fragments=frozen_param_fragments)
+        zero_model_states.append(z_model_state)
+
+    return zero_model_states
+
+
+def parse_optim_states(files, ds_checkpoint_dir):
+    total_files = len(files)
+    state_dicts = []
+    for f in files:
+        state_dict = torch.load(f, map_location=device)
+        # immediately discard the potentially huge 2 optimizer states as we only care for fp32 master weights
+        # and also handle the case where it was already removed by another helper script
+        state_dict["optimizer_state_dict"].pop("optimizer_state_dict", None)
+        state_dicts.append(state_dict)
+
+    if not ZERO_STAGE in state_dicts[0][OPTIMIZER_STATE_DICT]:
+        raise ValueError(f"{files[0]} is not a zero checkpoint")
+    zero_stage = state_dicts[0][OPTIMIZER_STATE_DICT][ZERO_STAGE]
+    world_size = state_dicts[0][OPTIMIZER_STATE_DICT][PARTITION_COUNT]
+
+    # For ZeRO-2 each param group can have different partition_count as data parallelism for expert
+    # parameters can be different from data parallelism for non-expert parameters. So we can just
+    # use the max of the partition_count to get the dp world_size.
+
+    if type(world_size) is list:
+        world_size = max(world_size)
+
+    if world_size != total_files:
+        raise ValueError(
+            f"Expected {world_size} of '*_optim_states.pt' under '{ds_checkpoint_dir}' but found {total_files} files. "
+            "Possibly due to an overwrite of an old checkpoint, or a checkpoint didn't get saved by one or more processes."
+        )
+
+    # the groups are named differently in each stage
+    if zero_stage <= 2:
+        fp32_groups_key = SINGLE_PARTITION_OF_FP32_GROUPS
+    elif zero_stage == 3:
+        fp32_groups_key = FP32_FLAT_GROUPS
+    else:
+        raise ValueError(f"unknown zero stage {zero_stage}")
+
+    if zero_stage <= 2:
+        fp32_flat_groups = [state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key] for i in range(len(state_dicts))]
+    elif zero_stage == 3:
+        # if there is more than one param group, there will be multiple flattened tensors - one
+        # flattened tensor per group - for simplicity merge them into a single tensor
+        #
+        # XXX: could make the script more memory efficient for when there are multiple groups - it
+        # will require matching the sub-lists of param_shapes for each param group flattened tensor
+
+        fp32_flat_groups = [
+            torch.cat(state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key], 0) for i in range(len(state_dicts))
+        ]
+
+    return zero_stage, world_size, fp32_flat_groups
+
+
+def _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters):
+    """
+    Returns fp32 state_dict reconstructed from ds checkpoint
+
+    Args:
+        - ``ds_checkpoint_dir``: path to the deepspeed checkpoint folder (where the optimizer files are)
+
+    """
+    print(f"Processing zero checkpoint '{ds_checkpoint_dir}'")
+
+    optim_files = get_optim_files(ds_checkpoint_dir)
+    zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir)
+    print(f"Detected checkpoint of type zero stage {zero_stage}, world_size: {world_size}")
+
+    model_files = get_model_state_files(ds_checkpoint_dir)
+
+    zero_model_states = parse_model_states(model_files)
+    print(f'Parsing checkpoint created by deepspeed=={zero_model_states[0].ds_version}')
+
+    if zero_stage <= 2:
+        return _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states,
+                                                          exclude_frozen_parameters)
+    elif zero_stage == 3:
+        return _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states,
+                                                          exclude_frozen_parameters)
+
+
+def _zero2_merge_frozen_params(state_dict, zero_model_states):
+    if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
+        return
+
+    frozen_param_shapes = zero_model_states[0].frozen_param_shapes
+    frozen_param_fragments = zero_model_states[0].frozen_param_fragments
+
+    if debug:
+        num_elem = sum(s.numel() for s in frozen_param_shapes.values())
+        print(f'rank 0: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
+
+        wanted_params = len(frozen_param_shapes)
+        wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
+        avail_numel = sum([p.numel() for p in frozen_param_fragments.values()])
+        print(f'Frozen params: Have {avail_numel} numels to process.')
+        print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
+
+    total_params = 0
+    total_numel = 0
+    for name, shape in frozen_param_shapes.items():
+        total_params += 1
+        unpartitioned_numel = shape.numel()
+        total_numel += unpartitioned_numel
+
+        state_dict[name] = frozen_param_fragments[name]
+
+        if debug:
+            print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
+
+    print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _has_callable(obj, fn):
+    attr = getattr(obj, fn, None)
+    return callable(attr)
+
+
+def _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
+    param_shapes = zero_model_states[0].param_shapes
+
+    # Reconstruction protocol:
+    #
+    # XXX: document this
+
+    if debug:
+        for i in range(world_size):
+            for j in range(len(fp32_flat_groups[0])):
+                print(f"{FP32_FLAT_GROUPS}[{i}][{j}].shape={fp32_flat_groups[i][j].shape}")
+
+    # XXX: memory usage doubles here (zero2)
+    num_param_groups = len(fp32_flat_groups[0])
+    merged_single_partition_of_fp32_groups = []
+    for i in range(num_param_groups):
+        merged_partitions = [sd[i] for sd in fp32_flat_groups]
+        full_single_fp32_vector = torch.cat(merged_partitions, 0)
+        merged_single_partition_of_fp32_groups.append(full_single_fp32_vector)
+    avail_numel = sum(
+        [full_single_fp32_vector.numel() for full_single_fp32_vector in merged_single_partition_of_fp32_groups])
+
+    if debug:
+        wanted_params = sum([len(shapes) for shapes in param_shapes])
+        wanted_numel = sum([sum(shape.numel() for shape in shapes.values()) for shapes in param_shapes])
+        # not asserting if there is a mismatch due to possible padding
+        print(f"Have {avail_numel} numels to process.")
+        print(f"Need {wanted_numel} numels in {wanted_params} params.")
+
+    # params
+    # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
+    # out-of-core computing solution
+    total_numel = 0
+    total_params = 0
+    for shapes, full_single_fp32_vector in zip(param_shapes, merged_single_partition_of_fp32_groups):
+        offset = 0
+        avail_numel = full_single_fp32_vector.numel()
+        for name, shape in shapes.items():
+
+            unpartitioned_numel = shape.numel() if _has_callable(shape, 'numel') else math.prod(shape)
+            total_numel += unpartitioned_numel
+            total_params += 1
+
+            if debug:
+                print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
+            state_dict[name] = full_single_fp32_vector.narrow(0, offset, unpartitioned_numel).view(shape)
+            offset += unpartitioned_numel
+
+        # Z2 started to align to 2*world_size to improve nccl performance. Therefore both offset and
+        # avail_numel can differ by anywhere between 0..2*world_size. Due to two unrelated complex
+        # paddings performed in the code it's almost impossible to predict the exact numbers w/o the
+        # live optimizer object, so we are checking that the numbers are within the right range
+        align_to = 2 * world_size
+
+        def zero2_align(x):
+            return align_to * math.ceil(x / align_to)
+
+        if debug:
+            print(f"original offset={offset}, avail_numel={avail_numel}")
+
+        offset = zero2_align(offset)
+        avail_numel = zero2_align(avail_numel)
+
+        if debug:
+            print(f"aligned  offset={offset}, avail_numel={avail_numel}")
+
+        # Sanity check
+        if offset != avail_numel:
+            raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
+
+    print(f"Reconstructed fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states,
+                                               exclude_frozen_parameters):
+    state_dict = OrderedDict()
+
+    # buffers
+    buffers = zero_model_states[0].buffers
+    state_dict.update(buffers)
+    if debug:
+        print(f"added {len(buffers)} buffers")
+
+    if not exclude_frozen_parameters:
+        _zero2_merge_frozen_params(state_dict, zero_model_states)
+
+    _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
+
+    # recover shared parameters
+    for pair in zero_model_states[0].shared_params:
+        if pair[1] in state_dict:
+            state_dict[pair[0]] = state_dict[pair[1]]
+
+    return state_dict
+
+
+def zero3_partitioned_param_info(unpartitioned_numel, world_size):
+    remainder = unpartitioned_numel % world_size
+    padding_numel = (world_size - remainder) if remainder else 0
+    partitioned_numel = math.ceil(unpartitioned_numel / world_size)
+    return partitioned_numel, padding_numel
+
+
+def _zero3_merge_frozen_params(state_dict, world_size, zero_model_states):
+    if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
+        return
+
+    if debug:
+        for i in range(world_size):
+            num_elem = sum(s.numel() for s in zero_model_states[i].frozen_param_fragments.values())
+            print(f'rank {i}: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
+
+        frozen_param_shapes = zero_model_states[0].frozen_param_shapes
+        wanted_params = len(frozen_param_shapes)
+        wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
+        avail_numel = sum([p.numel() for p in zero_model_states[0].frozen_param_fragments.values()]) * world_size
+        print(f'Frozen params: Have {avail_numel} numels to process.')
+        print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
+
+    total_params = 0
+    total_numel = 0
+    for name, shape in zero_model_states[0].frozen_param_shapes.items():
+        total_params += 1
+        unpartitioned_numel = shape.numel()
+        total_numel += unpartitioned_numel
+
+        param_frags = tuple(model_state.frozen_param_fragments[name] for model_state in zero_model_states)
+        state_dict[name] = torch.cat(param_frags, 0).narrow(0, 0, unpartitioned_numel).view(shape)
+
+        partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
+
+        if debug:
+            print(
+                f"Frozen params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
+            )
+
+    print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
+    param_shapes = zero_model_states[0].param_shapes
+    avail_numel = fp32_flat_groups[0].numel() * world_size
+    # Reconstruction protocol: For zero3 we need to zip the partitions together at boundary of each
+    # param, re-consolidating each param, while dealing with padding if any
+
+    # merge list of dicts, preserving order
+    param_shapes = {k: v for d in param_shapes for k, v in d.items()}
+
+    if debug:
+        for i in range(world_size):
+            print(f"{FP32_FLAT_GROUPS}[{i}].shape={fp32_flat_groups[i].shape}")
+
+        wanted_params = len(param_shapes)
+        wanted_numel = sum(shape.numel() for shape in param_shapes.values())
+        # not asserting if there is a mismatch due to possible padding
+        avail_numel = fp32_flat_groups[0].numel() * world_size
+        print(f"Trainable params: Have {avail_numel} numels to process.")
+        print(f"Trainable params: Need {wanted_numel} numels in {wanted_params} params.")
+
+    # params
+    # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
+    # out-of-core computing solution
+    offset = 0
+    total_numel = 0
+    total_params = 0
+    for name, shape in tqdm(param_shapes.items(), desc='Gathering Sharded Weights'):
+        unpartitioned_numel = shape.numel()
+        total_numel += unpartitioned_numel
+        total_params += 1
+        partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
+
+        if debug:
+            print(
+                f"Trainable params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
+            )
+
+        # XXX: memory usage doubles here
+        state_dict[name] = torch.cat(
+            tuple(fp32_flat_groups[i].narrow(0, offset, partitioned_numel) for i in range(world_size)),
+            0).narrow(0, 0, unpartitioned_numel).view(shape)
+        offset += partitioned_numel
+
+    offset *= world_size
+
+    # Sanity check
+    if offset != avail_numel:
+        raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
+
+    print(f"Reconstructed Trainable fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states,
+                                               exclude_frozen_parameters):
+    state_dict = OrderedDict()
+
+    # buffers
+    buffers = zero_model_states[0].buffers
+    state_dict.update(buffers)
+    if debug:
+        print(f"added {len(buffers)} buffers")
+
+    if not exclude_frozen_parameters:
+        _zero3_merge_frozen_params(state_dict, world_size, zero_model_states)
+
+    _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
+
+    # recover shared parameters
+    for pair in zero_model_states[0].shared_params:
+        if pair[1] in state_dict:
+            state_dict[pair[0]] = state_dict[pair[1]]
+
+    return state_dict
+
+
+def get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag=None, exclude_frozen_parameters=False):
+    """
+    Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated state_dict that can be loaded with
+    ``load_state_dict()`` and used for training without DeepSpeed or shared with others, for example
+    via a model hub.
+
+    Args:
+        - ``checkpoint_dir``: path to the desired checkpoint folder
+        - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in 'latest' file. e.g., ``global_step14``
+        - ``exclude_frozen_parameters``: exclude frozen parameters
+
+    Returns:
+        - pytorch ``state_dict``
+
+    Note: this approach may not work if your application doesn't have sufficient free CPU memory and
+    you may need to use the offline approach using the ``zero_to_fp32.py`` script that is saved with
+    the checkpoint.
+
+    A typical usage might be ::
+
+        from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint
+        # do the training and checkpoint saving
+        state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir) # already on cpu
+        model = model.cpu() # move to cpu
+        model.load_state_dict(state_dict)
+        # submit to model hub or save the model to share with others
+
+    In this example the ``model`` will no longer be usable in the deepspeed context of the same
+    application. i.e. you will need to re-initialize the deepspeed engine, since
+    ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
+
+    If you want it all done for you, use ``load_state_dict_from_zero_checkpoint`` instead.
+
+    """
+    if tag is None:
+        latest_path = os.path.join(checkpoint_dir, 'latest')
+        if os.path.isfile(latest_path):
+            with open(latest_path, 'r') as fd:
+                tag = fd.read().strip()
+        else:
+            raise ValueError(f"Unable to find 'latest' file at {latest_path}")
+
+    ds_checkpoint_dir = os.path.join(checkpoint_dir, tag)
+
+    if not os.path.isdir(ds_checkpoint_dir):
+        raise FileNotFoundError(f"Directory '{ds_checkpoint_dir}' doesn't exist")
+
+    return _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters)
+
+
+def convert_zero_checkpoint_to_fp32_state_dict(checkpoint_dir,
+                                               output_dir,
+                                               max_shard_size="5GB",
+                                               safe_serialization=False,
+                                               tag=None,
+                                               exclude_frozen_parameters=False):
+    """
+    Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` file that can be
+    loaded with ``torch.load(file)`` + ``load_state_dict()`` and used for training without DeepSpeed.
+
+    Args:
+        - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
+        - ``output_dir``: directory to the pytorch fp32 state_dict output files
+        - ``max_shard_size``: the maximum size for a checkpoint before being sharded, default value is 5GB
+        - ``safe_serialization``:  whether to save the model using `safetensors` or the traditional PyTorch way (that uses `pickle`).
+        - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
+        - ``exclude_frozen_parameters``: exclude frozen parameters
+    """
+    # Dependency pre-check
+    if safe_serialization:
+        try:
+            from safetensors.torch import save_file
+        except ImportError:
+            print('If you want to use `safe_serialization`, please `pip install safetensors`')
+            raise
+    if max_shard_size is not None:
+        try:
+            from huggingface_hub import split_torch_state_dict_into_shards
+        except ImportError:
+            print('If you want to use `max_shard_size`, please `pip install huggingface_hub`')
+            raise
+
+    # Convert zero checkpoint to state_dict
+    state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag, exclude_frozen_parameters)
+
+    # Shard the model if it is too big.
+    weights_name = "model.safetensors" if safe_serialization else "pytorch_model.bin"
+    if max_shard_size is not None:
+        filename_pattern = weights_name.replace(".bin", "{suffix}.bin").replace(".safetensors", "{suffix}.safetensors")
+        state_dict_split = split_torch_state_dict_into_shards(state_dict,
+                                                              filename_pattern=filename_pattern,
+                                                              max_shard_size=max_shard_size)
+    else:
+        from collections import namedtuple
+        StateDictSplit = namedtuple("StateDictSplit", ["is_sharded", "filename_to_tensors"])
+        state_dict_split = StateDictSplit(is_sharded=False,
+                                          filename_to_tensors={weights_name: list(state_dict.keys())})
+
+    # Save the model
+    filename_to_tensors = state_dict_split.filename_to_tensors.items()
+    for shard_file, tensors in tqdm(filename_to_tensors, desc="Saving checkpoint shards"):
+        shard = {tensor: state_dict[tensor].contiguous() for tensor in tensors}
+        output_path = os.path.join(output_dir, shard_file)
+        if safe_serialization:
+            save_file(shard, output_path, metadata={"format": "pt"})
+        else:
+            torch.save(shard, output_path)
+
+    # Save index if sharded
+    if state_dict_split.is_sharded:
+        index = {
+            "metadata": state_dict_split.metadata,
+            "weight_map": state_dict_split.tensor_to_filename,
+        }
+        save_index_file = "model.safetensors.index.json" if safe_serialization else "pytorch_model.bin.index.json"
+        save_index_file = os.path.join(output_dir, save_index_file)
+        with open(save_index_file, "w", encoding="utf-8") as f:
+            content = json.dumps(index, indent=2, sort_keys=True) + "\n"
+            f.write(content)
+
+
+def load_state_dict_from_zero_checkpoint(model, checkpoint_dir, tag=None):
+    """
+    1. Put the provided model to cpu
+    2. Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict``
+    3. Load it into the provided model
+
+    Args:
+        - ``model``: the model object to update
+        - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
+        - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
+
+    Returns:
+        - ``model`: modified model
+
+    Make sure you have plenty of CPU memory available before you call this function. If you don't
+    have enough use the ``zero_to_fp32.py`` utility to do the conversion. You will find it
+    conveniently placed for you in the checkpoint folder.
+
+    A typical usage might be ::
+
+        from deepspeed.utils.zero_to_fp32 import load_state_dict_from_zero_checkpoint
+        model = load_state_dict_from_zero_checkpoint(trainer.model, checkpoint_dir)
+        # submit to model hub or save the model to share with others
+
+    Note, that once this was run, the ``model`` will no longer be usable in the deepspeed context
+    of the same application. i.e. you will need to re-initialize the deepspeed engine, since
+    ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
+
+    """
+    logger.info(f"Extracting fp32 weights")
+    state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
+
+    logger.info(f"Overwriting model with fp32 weights")
+    model = model.cpu()
+    model.load_state_dict(state_dict, strict=False)
+
+    return model
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("checkpoint_dir",
+                        type=str,
+                        help="path to the desired checkpoint folder, e.g., path/checkpoint-12")
+    parser.add_argument("output_dir",
+                        type=str,
+                        help="directory to the pytorch fp32 state_dict output files"
+                        "(e.g. path/checkpoint-12-output/)")
+    parser.add_argument(
+        "--max_shard_size",
+        type=str,
+        default="5GB",
+        help="The maximum size for a checkpoint before being sharded. Checkpoints shard will then be each of size"
+        "lower than this size. If expressed as a string, needs to be digits followed by a unit (like `5MB`"
+        "We default it to 5GB in order for models to be able to run easily on free-tier google colab instances"
+        "without CPU OOM issues.")
+    parser.add_argument(
+        "--safe_serialization",
+        default=False,
+        action='store_true',
+        help="Whether to save the model using `safetensors` or the traditional PyTorch way (that uses `pickle`).")
+    parser.add_argument("-t",
+                        "--tag",
+                        type=str,
+                        default=None,
+                        help="checkpoint tag used as a unique identifier for checkpoint. e.g., global_step1")
+    parser.add_argument("--exclude_frozen_parameters", action='store_true', help="exclude frozen parameters")
+    parser.add_argument("-d", "--debug", action='store_true', help="enable debug")
+    args = parser.parse_args()
+
+    debug = args.debug
+
+    convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir,
+                                               args.output_dir,
+                                               max_shard_size=args.max_shard_size,
+                                               safe_serialization=args.safe_serialization,
+                                               tag=args.tag,
+                                               exclude_frozen_parameters=args.exclude_frozen_parameters)

config.json

@@ -0,0 +1,66 @@
+{
+  "_name_or_path": "llava-hf/llava-v1.6-mistral-7b-hf",
+  "architectures": [
+    "LlavaNextForConditionalGeneration"
+  ],
+  "ignore_index": -100,
+  "image_grid_pinpoints": [
+    [
+      336,
+      672
+    ],
+    [
+      672,
+      336
+    ],
+    [
+      672,
+      672
+    ],
+    [
+      1008,
+      336
+    ],
+    [
+      336,
+      1008
+    ]
+  ],
+  "image_seq_length": 576,
+  "image_token_index": 32000,
+  "model_type": "llava_next",
+  "projector_hidden_act": "gelu",
+  "text_config": {
+    "_name_or_path": "mistralai/Mistral-7B-Instruct-v0.2",
+    "architectures": [
+      "MistralForCausalLM"
+    ],
+    "intermediate_size": 14336,
+    "max_position_embeddings": 32768,
+    "model_type": "mistral",
+    "num_key_value_heads": 8,
+    "rms_norm_eps": 1e-05,
+    "rope_theta": 1000000.0,
+    "sliding_window": null,
+    "torch_dtype": "bfloat16",
+    "vocab_size": 32064
+  },
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.46.0",
+  "use_image_newline_parameter": true,
+  "vision_config": {
+    "hidden_size": 1024,
+    "image_size": 336,
+    "intermediate_size": 4096,
+    "model_type": "clip_vision_model",
+    "num_attention_heads": 16,
+    "num_hidden_layers": 24,
+    "patch_size": 14,
+    "projection_dim": 768,
+    "vocab_size": 32000
+  },
+  "vision_feature_layer": -2,
+  "vision_feature_select_strategy": "default",
+  "vocab_size": 32064
+}

generation_config.json

@@ -0,0 +1,6 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.46.0"
+}

lorra_config.json

@@ -0,0 +1,8 @@
+{
+  "target_layers": "16",
+  "transform_layers": "14,15,16",
+  "lorra_alpha": 5.0,
+  "trainsets": null,
+  "valsets": null,
+  "full_layers": false
+}

preprocessor_config.json

@@ -0,0 +1,52 @@
+{
+  "aspect_ratio_setting": "anyres",
+  "crop_size": {
+    "height": 336,
+    "width": 336
+  },
+  "do_center_crop": true,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_pad": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_grid_pinpoints": [
+    [
+      336,
+      672
+    ],
+    [
+      672,
+      336
+    ],
+    [
+      672,
+      672
+    ],
+    [
+      1008,
+      336
+    ],
+    [
+      336,
+      1008
+    ]
+  ],
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_processor_type": "LlavaNextImageProcessor",
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "processor_class": "LlavaNextProcessor",
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 336
+  }
+}

processor_config.json

@@ -0,0 +1,6 @@
+{
+  "image_token": "<image>",
+  "patch_size": 14,
+  "processor_class": "LlavaNextProcessor",
+  "vision_feature_select_strategy": "default"
+}

pytorch_model-00001-of-00005.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a7447bdce00f6c94829b02860b0b1f642f10ca1ba64f8dae193d21a200540b6f
+size 3080245101

pytorch_model-00002-of-00005.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d9b6ca3ea95f075e46c42c0bb2515928e5c75f67cb5c969cd5c04667c7c7ac30
+size 4915941642

pytorch_model-00003-of-00005.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6c90dda441fde80d55b33378941ceaa0742530218ddae4fa767d1d384fbc5c63
+size 4915941642

pytorch_model-00004-of-00005.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e588585a2e0d5cf8a9062b99da12da2ff9134a6740d89fd24ad680dfa4b84342
+size 2298601226

pytorch_model-00005-of-00005.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3c9eee75efce5195c70fda1aa47a0fd6030b23f07679a8922b24765fa400281f
+size 262681110

pytorch_model.bin.index.json

@@ -0,0 +1,829 @@
+{
+  "metadata": {
+    "total_size": 21676855296
+  },
+  "weight_map": {
+    "image_newline": "pytorch_model-00001-of-00005.bin",
+    "language_model.lm_head.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.embed_tokens.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.0.input_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.0.mlp.down_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.0.mlp.gate_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.0.mlp.up_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.0.post_attention_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.0.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.0.self_attn.o_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.0.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.0.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.1.input_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.1.mlp.down_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.1.mlp.gate_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.1.mlp.up_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.1.post_attention_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.1.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.1.self_attn.o_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.1.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.1.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.10.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.10.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.10.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.10.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.10.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.10.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.10.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.10.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.10.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.11.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.11.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.11.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.11.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.11.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.11.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.11.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.11.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.11.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.12.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.12.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.12.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.12.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.12.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.12.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.12.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.12.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.12.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.13.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.13.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.13.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.13.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.13.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.13.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.13.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.13.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.13.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.14.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.14.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.14.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.14.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.14.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.14.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.14.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.14.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.14.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.15.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.15.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.15.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.15.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.15.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.15.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.15.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.15.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.15.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.16.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.16.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.16.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.16.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.16.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.16.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.16.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.16.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.16.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.17.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.17.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.17.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.17.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.17.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.17.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.17.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.17.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.17.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.18.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.18.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.18.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.18.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.18.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.18.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.18.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.18.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.18.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.19.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.19.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.19.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.19.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.19.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.19.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.19.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.19.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.19.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.2.input_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.2.mlp.down_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.2.mlp.gate_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.2.mlp.up_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.2.post_attention_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.2.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.2.self_attn.o_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.2.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.2.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.20.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.20.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.20.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.20.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.20.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.20.self_attn.k_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.20.self_attn.o_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.20.self_attn.q_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.20.self_attn.v_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.21.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.21.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.21.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.21.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.21.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.21.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.21.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.21.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.21.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.22.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.22.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.22.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.22.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.22.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.22.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.22.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.22.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.22.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.23.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.23.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.23.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.23.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.23.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.23.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.23.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.23.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.23.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.24.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.24.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.24.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.24.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.24.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.24.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.24.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.24.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.24.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.25.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.25.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.25.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.25.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.25.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.25.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.25.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.25.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.25.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.26.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.26.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.26.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.26.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.26.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.26.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.26.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.26.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.26.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.27.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.27.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.27.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.27.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.27.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.27.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.27.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.27.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.27.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.28.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.28.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.28.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.28.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.28.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.28.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.28.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.28.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.28.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.29.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.29.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.29.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.29.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.29.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.29.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.29.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.29.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.29.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.3.input_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.3.mlp.down_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.3.mlp.gate_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.3.mlp.up_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.3.post_attention_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.3.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.3.self_attn.o_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.3.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.3.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.30.input_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.30.mlp.down_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.30.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.30.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.30.post_attention_layernorm.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.30.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.30.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.30.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.30.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.31.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.31.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.31.mlp.gate_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.31.mlp.up_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.31.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.31.self_attn.k_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.31.self_attn.o_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.31.self_attn.q_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.31.self_attn.v_proj.weight": "pytorch_model-00003-of-00005.bin",
+    "language_model.model.layers.32.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.32.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.32.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.32.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.32.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.32.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.32.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.32.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.32.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.33.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.33.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.33.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.33.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.33.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.33.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.33.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.33.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.33.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.34.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.34.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.34.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.34.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.34.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.34.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.34.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.34.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.34.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.35.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.35.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.35.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.35.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.35.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.35.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.35.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.35.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.35.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.36.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.36.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.36.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.36.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.36.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.36.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.36.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.36.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.36.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.37.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.37.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.37.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.37.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.37.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.37.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.37.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.37.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.37.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.38.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.38.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.38.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.38.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.38.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.38.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.38.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.38.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.38.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.39.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.39.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.39.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.39.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.39.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.39.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.39.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.39.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.39.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.4.input_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.4.mlp.down_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.4.mlp.gate_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.4.mlp.up_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.4.post_attention_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.4.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.4.self_attn.o_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.4.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.4.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.40.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.40.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.40.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.40.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.40.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.40.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.40.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.40.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.40.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.41.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.41.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.41.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.41.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.41.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.41.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.41.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.41.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.41.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.42.input_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.42.mlp.down_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.42.mlp.gate_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.42.mlp.up_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.42.post_attention_layernorm.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.42.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.42.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.42.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.42.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.43.input_layernorm.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.43.mlp.down_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.43.mlp.gate_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.43.mlp.up_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.43.post_attention_layernorm.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.43.self_attn.k_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.43.self_attn.o_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.43.self_attn.q_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.43.self_attn.v_proj.weight": "pytorch_model-00004-of-00005.bin",
+    "language_model.model.layers.44.input_layernorm.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.44.mlp.down_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.44.mlp.gate_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.44.mlp.up_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.44.post_attention_layernorm.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.44.self_attn.k_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.44.self_attn.o_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.44.self_attn.q_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.44.self_attn.v_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.45.input_layernorm.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.45.mlp.down_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.45.mlp.gate_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.45.mlp.up_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.45.post_attention_layernorm.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.45.self_attn.k_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.45.self_attn.o_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.45.self_attn.q_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.45.self_attn.v_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.46.input_layernorm.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.46.mlp.down_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.46.mlp.gate_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.46.mlp.up_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.46.post_attention_layernorm.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.46.self_attn.k_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.46.self_attn.o_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.46.self_attn.q_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.46.self_attn.v_proj.weight": "pytorch_model-00005-of-00005.bin",
+    "language_model.model.layers.5.input_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.5.mlp.down_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.5.mlp.gate_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.5.mlp.up_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.5.post_attention_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.5.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.5.self_attn.o_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.5.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.5.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.6.input_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.6.mlp.down_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.6.mlp.gate_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.6.mlp.up_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.6.post_attention_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.6.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.6.self_attn.o_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.6.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.6.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.7.input_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.7.mlp.down_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.7.mlp.gate_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.7.mlp.up_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.7.post_attention_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.7.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.7.self_attn.o_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.7.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.7.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.8.input_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.8.mlp.down_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.8.mlp.gate_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.8.mlp.up_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.8.post_attention_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.8.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.8.self_attn.o_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.8.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.8.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.9.input_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.9.mlp.down_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.9.mlp.gate_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.9.mlp.up_proj.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.9.post_attention_layernorm.weight": "pytorch_model-00002-of-00005.bin",
+    "language_model.model.layers.9.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.9.self_attn.o_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.9.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "language_model.model.norm.weight": "pytorch_model-00005-of-00005.bin",
+    "multi_modal_projector.linear_1.bias": "pytorch_model-00001-of-00005.bin",
+    "multi_modal_projector.linear_1.weight": "pytorch_model-00001-of-00005.bin",
+    "multi_modal_projector.linear_2.bias": "pytorch_model-00001-of-00005.bin",
+    "multi_modal_projector.linear_2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.embeddings.class_embedding": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.embeddings.patch_embedding.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.embeddings.position_embedding.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.0.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.1.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.10.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.11.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.12.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.13.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.14.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.15.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.16.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.17.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.18.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.19.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.2.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.20.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.21.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.22.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.23.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.3.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.4.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.5.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.6.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.7.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.8.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.layer_norm1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.layer_norm1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.layer_norm2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.layer_norm2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.mlp.fc1.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.mlp.fc1.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.mlp.fc2.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.mlp.fc2.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.self_attn.k_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.self_attn.k_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.self_attn.out_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.self_attn.out_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.self_attn.q_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.self_attn.q_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.self_attn.v_proj.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.encoder.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.post_layernorm.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.post_layernorm.weight": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.pre_layrnorm.bias": "pytorch_model-00001-of-00005.bin",
+    "vision_tower.vision_model.pre_layrnorm.weight": "pytorch_model-00001-of-00005.bin"
+  }
+}

special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "</s>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
+size 493443

tokenizer_config.json

@@ -0,0 +1,69 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32000": {
+      "content": "<image>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32001": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "extra_special_tokens": {
+    "image_token": "<image>"
+  },
+  "image_token": "<image>",
+  "legacy": true,
+  "max_length": null,
+  "model_max_length": 8192,
+  "pad_to_multiple_of": null,
+  "pad_token": "</s>",
+  "pad_token_type_id": 0,
+  "padding_side": "left",
+  "processor_class": "LlavaNextProcessor",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b687191320ebcf3b23eba17022227dbbdb99144f49afde09c51ab32e4eacc1f2
+size 6840