Upload folder using huggingface_hub

README.md

@@ -0,0 +1,40 @@
+---
+tags:
+- autotrain
+- text-generation
+widget:
+- text: "I love AutoTrain because "
+license: other
+---
+
+# Model Trained Using AutoTrain
+
+This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
+
+# Usage
+
+```python
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_path = "PATH_TO_THIS_REPO"
+
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForCausalLM.from_pretrained(
+    model_path,
+    device_map="auto",
+    torch_dtype='auto'
+).eval()
+
+# Prompt content: "hi"
+messages = [
+    {"role": "user", "content": "hi"}
+]
+
+input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
+output_ids = model.generate(input_ids.to('cuda'))
+response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
+
+# Model response: "Hello! How can I assist you today?"
+print(response)
+```

adapter_config.json

@@ -0,0 +1,32 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "cognitivecomputations/dolphin-2.2.1-mistral-7b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "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": [
+    "gate_proj",
+    "down_proj",
+    "o_proj",
+    "q_proj",
+    "up_proj",
+    "k_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6862dc5a93fdc6ea05550dd6e472a5bf43bc6f83a650d029e31a148fa9480b9
+size 167832240

added_tokens.json

@@ -0,0 +1,4 @@
+{
+  "<|im_end|>": 32000,
+  "<|im_start|>": 32001
+}

checkpoint-500/README.md

@@ -0,0 +1,204 @@
+---
+library_name: peft
+base_model: cognitivecomputations/dolphin-2.2.1-mistral-7b
+---
+
+# 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 0.8.2

checkpoint-500/adapter_config.json

@@ -0,0 +1,32 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "cognitivecomputations/dolphin-2.2.1-mistral-7b",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "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": [
+    "gate_proj",
+    "down_proj",
+    "o_proj",
+    "q_proj",
+    "up_proj",
+    "k_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

checkpoint-500/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6862dc5a93fdc6ea05550dd6e472a5bf43bc6f83a650d029e31a148fa9480b9
+size 167832240

checkpoint-500/added_tokens.json

@@ -0,0 +1,4 @@
+{
+  "<|im_end|>": 32000,
+  "<|im_start|>": 32001
+}

checkpoint-500/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:597ba2e5971b143dbf61112508296f7bc199f04fc1ad6310b7986b6c40b24eb0
+size 335922386

checkpoint-500/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6b55a2b068303a7e41a49339999351c52e3e90488edc2f0a4cca65fa9e1368e
+size 14244

checkpoint-500/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:38232a22bfcd3f3c254ba824b2144254da8ba209642f840adbaf0b8a0079b16d
+size 1064

checkpoint-500/special_tokens_map.json

@@ -0,0 +1,30 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

checkpoint-500/tokenizer.model

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

checkpoint-500/tokenizer_config.json

@@ -0,0 +1,62 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": true,
+  "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": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32001": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "legacy": true,
+  "model_max_length": 2048,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "trust_remote_code": false,
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true,
+  "use_fast": true
+}

checkpoint-500/trainer_state.json

@@ -0,0 +1,406 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 100.0,
+  "eval_steps": 500,
+  "global_step": 500,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 1.8,
+      "grad_norm": 2.1598100662231445,
+      "learning_rate": 5.399999999999999e-05,
+      "loss": 1.2357,
+      "step": 9
+    },
+    {
+      "epoch": 3.6,
+      "grad_norm": 1.948647379875183,
+      "learning_rate": 0.00010799999999999998,
+      "loss": 0.6636,
+      "step": 18
+    },
+    {
+      "epoch": 5.4,
+      "grad_norm": 1.9161983728408813,
+      "learning_rate": 0.000162,
+      "loss": 0.2845,
+      "step": 27
+    },
+    {
+      "epoch": 7.2,
+      "grad_norm": 0.49437546730041504,
+      "learning_rate": 0.00021599999999999996,
+      "loss": 0.0769,
+      "step": 36
+    },
+    {
+      "epoch": 9.0,
+      "grad_norm": 1.0303442478179932,
+      "learning_rate": 0.000258,
+      "loss": 0.0496,
+      "step": 45
+    },
+    {
+      "epoch": 10.8,
+      "grad_norm": 0.9161431193351746,
+      "learning_rate": 0.00029866666666666664,
+      "loss": 0.0414,
+      "step": 54
+    },
+    {
+      "epoch": 12.6,
+      "grad_norm": 1.0928488969802856,
+      "learning_rate": 0.0002926666666666666,
+      "loss": 0.032,
+      "step": 63
+    },
+    {
+      "epoch": 14.4,
+      "grad_norm": 0.9965436458587646,
+      "learning_rate": 0.0002866666666666667,
+      "loss": 0.0214,
+      "step": 72
+    },
+    {
+      "epoch": 16.2,
+      "grad_norm": 0.3007476329803467,
+      "learning_rate": 0.00028066666666666664,
+      "loss": 0.0322,
+      "step": 81
+    },
+    {
+      "epoch": 18.0,
+      "grad_norm": NaN,
+      "learning_rate": 0.000276,
+      "loss": 0.098,
+      "step": 90
+    },
+    {
+      "epoch": 19.8,
+      "grad_norm": 0.671339750289917,
+      "learning_rate": 0.00027133333333333333,
+      "loss": 0.1021,
+      "step": 99
+    },
+    {
+      "epoch": 21.6,
+      "grad_norm": 0.4084804952144623,
+      "learning_rate": 0.0002653333333333333,
+      "loss": 0.0119,
+      "step": 108
+    },
+    {
+      "epoch": 23.4,
+      "grad_norm": 0.37794339656829834,
+      "learning_rate": 0.0002593333333333333,
+      "loss": 0.0127,
+      "step": 117
+    },
+    {
+      "epoch": 25.2,
+      "grad_norm": 0.38235852122306824,
+      "learning_rate": 0.00025333333333333333,
+      "loss": 0.0123,
+      "step": 126
+    },
+    {
+      "epoch": 27.0,
+      "grad_norm": 0.390073299407959,
+      "learning_rate": 0.0002473333333333333,
+      "loss": 0.0045,
+      "step": 135
+    },
+    {
+      "epoch": 28.8,
+      "grad_norm": 0.4367002844810486,
+      "learning_rate": 0.0002413333333333333,
+      "loss": 0.0063,
+      "step": 144
+    },
+    {
+      "epoch": 30.6,
+      "grad_norm": 0.42980659008026123,
+      "learning_rate": 0.00023533333333333333,
+      "loss": 0.0049,
+      "step": 153
+    },
+    {
+      "epoch": 32.4,
+      "grad_norm": 0.20197640359401703,
+      "learning_rate": 0.00022933333333333332,
+      "loss": 0.0068,
+      "step": 162
+    },
+    {
+      "epoch": 34.2,
+      "grad_norm": 0.07533933967351913,
+      "learning_rate": 0.00022333333333333333,
+      "loss": 0.004,
+      "step": 171
+    },
+    {
+      "epoch": 36.0,
+      "grad_norm": 0.0386396124958992,
+      "learning_rate": 0.00021733333333333332,
+      "loss": 0.0037,
+      "step": 180
+    },
+    {
+      "epoch": 37.8,
+      "grad_norm": 0.0207373034209013,
+      "learning_rate": 0.0002113333333333333,
+      "loss": 0.0018,
+      "step": 189
+    },
+    {
+      "epoch": 39.6,
+      "grad_norm": 0.06749772280454636,
+      "learning_rate": 0.0002053333333333333,
+      "loss": 0.0006,
+      "step": 198
+    },
+    {
+      "epoch": 41.4,
+      "grad_norm": 0.010618847794830799,
+      "learning_rate": 0.0001993333333333333,
+      "loss": 0.0003,
+      "step": 207
+    },
+    {
+      "epoch": 43.2,
+      "grad_norm": 0.0014326042728498578,
+      "learning_rate": 0.00019333333333333333,
+      "loss": 0.0003,
+      "step": 216
+    },
+    {
+      "epoch": 45.0,
+      "grad_norm": 0.06165959686040878,
+      "learning_rate": 0.00018733333333333332,
+      "loss": 0.0003,
+      "step": 225
+    },
+    {
+      "epoch": 46.8,
+      "grad_norm": 0.0007684020092710853,
+      "learning_rate": 0.00018133333333333331,
+      "loss": 0.0002,
+      "step": 234
+    },
+    {
+      "epoch": 48.6,
+      "grad_norm": 0.0010787370847538114,
+      "learning_rate": 0.0001753333333333333,
+      "loss": 0.0002,
+      "step": 243
+    },
+    {
+      "epoch": 50.4,
+      "grad_norm": 0.0032115266658365726,
+      "learning_rate": 0.00016933333333333332,
+      "loss": 0.0003,
+      "step": 252
+    },
+    {
+      "epoch": 52.2,
+      "grad_norm": 0.0009848058689385653,
+      "learning_rate": 0.0001633333333333333,
+      "loss": 0.0002,
+      "step": 261
+    },
+    {
+      "epoch": 54.0,
+      "grad_norm": 0.000787117169238627,
+      "learning_rate": 0.00015733333333333333,
+      "loss": 0.0007,
+      "step": 270
+    },
+    {
+      "epoch": 55.8,
+      "grad_norm": 0.0012765954015776515,
+      "learning_rate": 0.00015133333333333332,
+      "loss": 0.0002,
+      "step": 279
+    },
+    {
+      "epoch": 57.6,
+      "grad_norm": 0.05409696698188782,
+      "learning_rate": 0.00014533333333333333,
+      "loss": 0.0002,
+      "step": 288
+    },
+    {
+      "epoch": 59.4,
+      "grad_norm": 0.04873191937804222,
+      "learning_rate": 0.00013933333333333332,
+      "loss": 0.0003,
+      "step": 297
+    },
+    {
+      "epoch": 61.2,
+      "grad_norm": 0.0004421588673721999,
+      "learning_rate": 0.0001333333333333333,
+      "loss": 0.0006,
+      "step": 306
+    },
+    {
+      "epoch": 63.0,
+      "grad_norm": 0.0011476241052150726,
+      "learning_rate": 0.00012733333333333333,
+      "loss": 0.0003,
+      "step": 315
+    },
+    {
+      "epoch": 64.8,
+      "grad_norm": 0.0005729855038225651,
+      "learning_rate": 0.00012133333333333332,
+      "loss": 0.0002,
+      "step": 324
+    },
+    {
+      "epoch": 66.6,
+      "grad_norm": 0.0586007684469223,
+      "learning_rate": 0.00011533333333333332,
+      "loss": 0.0006,
+      "step": 333
+    },
+    {
+      "epoch": 68.4,
+      "grad_norm": 0.0006001991569064558,
+      "learning_rate": 0.00010933333333333333,
+      "loss": 0.0002,
+      "step": 342
+    },
+    {
+      "epoch": 70.2,
+      "grad_norm": 0.03952179476618767,
+      "learning_rate": 0.00010333333333333333,
+      "loss": 0.0002,
+      "step": 351
+    },
+    {
+      "epoch": 72.0,
+      "grad_norm": 0.06108314171433449,
+      "learning_rate": 9.733333333333332e-05,
+      "loss": 0.0002,
+      "step": 360
+    },
+    {
+      "epoch": 73.8,
+      "grad_norm": 0.00037649282603524625,
+      "learning_rate": 9.133333333333334e-05,
+      "loss": 0.0002,
+      "step": 369
+    },
+    {
+      "epoch": 75.6,
+      "grad_norm": 0.001120861852541566,
+      "learning_rate": 8.533333333333332e-05,
+      "loss": 0.0001,
+      "step": 378
+    },
+    {
+      "epoch": 77.4,
+      "grad_norm": 0.004925732500851154,
+      "learning_rate": 7.933333333333331e-05,
+      "loss": 0.0003,
+      "step": 387
+    },
+    {
+      "epoch": 79.2,
+      "grad_norm": 0.0009467621566727757,
+      "learning_rate": 7.333333333333332e-05,
+      "loss": 0.0001,
+      "step": 396
+    },
+    {
+      "epoch": 81.0,
+      "grad_norm": 0.0015193276340141892,
+      "learning_rate": 6.733333333333333e-05,
+      "loss": 0.0002,
+      "step": 405
+    },
+    {
+      "epoch": 82.8,
+      "grad_norm": 0.00035535290953703225,
+      "learning_rate": 6.133333333333334e-05,
+      "loss": 0.0002,
+      "step": 414
+    },
+    {
+      "epoch": 84.6,
+      "grad_norm": 0.041585084050893784,
+      "learning_rate": 5.533333333333333e-05,
+      "loss": 0.0002,
+      "step": 423
+    },
+    {
+      "epoch": 86.4,
+      "grad_norm": 0.0007830450776964426,
+      "learning_rate": 4.933333333333333e-05,
+      "loss": 0.0001,
+      "step": 432
+    },
+    {
+      "epoch": 88.2,
+      "grad_norm": 0.024977711960673332,
+      "learning_rate": 4.333333333333333e-05,
+      "loss": 0.0002,
+      "step": 441
+    },
+    {
+      "epoch": 90.0,
+      "grad_norm": 0.00046858747373335063,
+      "learning_rate": 3.733333333333333e-05,
+      "loss": 0.0002,
+      "step": 450
+    },
+    {
+      "epoch": 91.8,
+      "grad_norm": 0.04403144493699074,
+      "learning_rate": 3.1333333333333334e-05,
+      "loss": 0.0002,
+      "step": 459
+    },
+    {
+      "epoch": 93.6,
+      "grad_norm": 0.037283509969711304,
+      "learning_rate": 2.533333333333333e-05,
+      "loss": 0.0002,
+      "step": 468
+    },
+    {
+      "epoch": 95.4,
+      "grad_norm": 0.0004454792069736868,
+      "learning_rate": 1.933333333333333e-05,
+      "loss": 0.0002,
+      "step": 477
+    },
+    {
+      "epoch": 97.2,
+      "grad_norm": 0.03768078610301018,
+      "learning_rate": 1.3333333333333333e-05,
+      "loss": 0.0001,
+      "step": 486
+    },
+    {
+      "epoch": 99.0,
+      "grad_norm": 0.035461634397506714,
+      "learning_rate": 7.333333333333333e-06,
+      "loss": 0.0001,
+      "step": 495
+    }
+  ],
+  "logging_steps": 9,
+  "max_steps": 500,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 100,
+  "save_steps": 500,
+  "total_flos": 4.3945643999232e+16,
+  "train_batch_size": 2,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-500/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f6ef03a53fdd28af57b9913c809990cb4103103c81c4f6a299091b217944061f
+size 4920

handler.py

@@ -0,0 +1,32 @@
+from typing import  Dict, List, Any
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import torch
+from peft import PeftModel
+import json
+import os
+
+
+class EndpointHandler():
+    def __init__(self, path=""):
+        base_model_path = json.load(open(os.path.join(path, "training_params.json")))["model"]
+        model = AutoModelForCausalLM.from_pretrained(
+            base_model_path,
+            torch_dtype=torch.float16,
+            low_cpu_mem_usage=True,
+            trust_remote_code=True,
+            device_map="auto",
+        )
+        tokenizer = AutoTokenizer.from_pretrained(path, trust_remote_code=True)
+        model.resize_token_embeddings(len(tokenizer))
+        model = PeftModel.from_pretrained(model, path)
+        model = model.merge_and_unload()
+        self.pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+    def __call__(self, data: Any) -> List[List[Dict[str, float]]]:
+        inputs = data.pop("inputs", data)
+        parameters = data.pop("parameters", None)
+        if parameters is not None:
+            prediction = self.pipeline(inputs, **parameters)
+        else:
+            prediction = self.pipeline(inputs)
+        return prediction

requirements.txt

@@ -0,0 +1,2 @@
+peft==0.8.2
+transformers==4.37.0

runs/Feb25_12-28-14_r-codesagar-prompt-guard-bw3akjco-f5b5d-3guve/events.out.tfevents.1708864095.r-codesagar-prompt-guard-bw3akjco-f5b5d-3guve.97.0

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5f4651429b8e0c5f5969b6bf460f503e84cedd33d0e5e7e7dcf13bd312a2de9b
+size 16974

special_tokens_map.json

@@ -0,0 +1,30 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "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 +1,62 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": true,
+  "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": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32001": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "legacy": true,
+  "model_max_length": 2048,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "trust_remote_code": false,
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true,
+  "use_fast": true
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f6ef03a53fdd28af57b9913c809990cb4103103c81c4f6a299091b217944061f
+size 4920

training_params.json

@@ -0,0 +1,47 @@
+{
+    "model": "cognitivecomputations/dolphin-2.2.1-mistral-7b",
+    "project_name": "autotrain-ugs12-98r1b",
+    "data_path": "autotrain-ugs12-98r1b/autotrain-data",
+    "train_split": "train",
+    "valid_split": null,
+    "add_eos_token": true,
+    "block_size": 1024,
+    "model_max_length": 2048,
+    "padding": "right",
+    "trainer": "sft",
+    "use_flash_attention_2": false,
+    "log": "tensorboard",
+    "disable_gradient_checkpointing": false,
+    "logging_steps": -1,
+    "evaluation_strategy": "epoch",
+    "save_total_limit": 1,
+    "save_strategy": "epoch",
+    "auto_find_batch_size": false,
+    "mixed_precision": "fp16",
+    "lr": 0.0003,
+    "epochs": 100,
+    "batch_size": 2,
+    "warmup_ratio": 0.1,
+    "gradient_accumulation": 1,
+    "optimizer": "adamw_torch",
+    "scheduler": "linear",
+    "weight_decay": 0.0,
+    "max_grad_norm": 1.0,
+    "seed": 42,
+    "chat_template": "none",
+    "quantization": "int4",
+    "target_modules": "all-linear",
+    "merge_adapter": false,
+    "peft": true,
+    "lora_r": 16,
+    "lora_alpha": 32,
+    "lora_dropout": 0.05,
+    "model_ref": null,
+    "dpo_beta": 0.1,
+    "prompt_text_column": "autotrain_prompt",
+    "text_column": "autotrain_text",
+    "rejected_text_column": "autotrain_rejected_text",
+    "push_to_hub": true,
+    "repo_id": "codesagar/autotrain-ugs12-98r1b",
+    "username": "codesagar"
+}