metadata
license: other
license_name: tongyi-qianwen
license_link: https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE
pipeline_tag: text-generation
language:
- en
- zh
library_name: transformers
tags:
- mergekit
- llama
IridiumLlama-72B-v0.1
Model Description
IridiumLlama is a 72B parameter language model created through a merge of Qwen2-72B-Instruct, calme2.1-72b, and magnum-72b-v1 using model_stock.
This is converted from leafspark/Iridium-72B-v0.1 (currently private)
Features
- 72 billion parameters
- Sharded in 31 files (unlike Iridium, which has 963 shards due to the merging process)
- Combines Magnum prose with Calam smarts
- Llamaified for easy use
Technical Specifications
Architecture
LlamaForCasualLM- Models: Qwen2-72B-Instruct (base), calme2.1-72b, magnum-72b-v1
- Merged layers: 80
- Total tensors: 1,043
- Context length: 32k
Tensor Distribution
- Attention layers: 560 files
- MLP layers: 240 files
- Layer norms: 160 files
- Miscellaneous (embeddings, output): 162 files
Merging
Custom script utilizing safetensors library.
Usage
Loading the Model
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model = AutoModelForCausalLM.from_pretrained("leafspark/IridiumLlama-72B-v0.1",
device_map="auto",
torch_dtype=torch.float16)
tokenizer = AutoTokenizer.from_pretrained("leafspark/IridiumLlama-72B-v0.1")
GGUFs
Find them here: mradermacher/IridiumLlama-72B-v0.1-GGUF
Hardware Requirements
- At least ~150GB of free space
- ~150GB VRAM