prithivMLmods's picture
Update README.md
06f0076 verified
metadata
license: creativeml-openrail-m
datasets:
  - amphora/QwQ-LongCoT-130K
language:
  - en
base_model:
  - Qwen/Qwen2.5-7B-Instruct
pipeline_tag: text-generation
library_name: transformers
tags:
  - Long-CoT
  - Qwen2.5
  - 7B
  - safetensors
  - text-generation-inference
  - QwQ
  - SFT
  - Math
  - Qwen with Questions

QwQ-LCoT-7B-Instruct Model File

The QwQ-LCoT-7B-Instruct is a fine-tuned language model designed for advanced reasoning and instruction-following tasks. It leverages the Qwen2.5-7B base model and has been fine-tuned on the amphora/QwQ-LongCoT-130K dataset, focusing on chain-of-thought (CoT) reasoning.

File Name Size Description Upload Status
.gitattributes 1.57 kB Tracks large files with Git LFS. Uploaded
README.md 273 Bytes Contains initial documentation, likely minimal. Updated
added_tokens.json 657 Bytes Maps additional tokens for the tokenizer. Uploaded
config.json 848 Bytes Model configuration (basic setup). Uploaded
generation_config.json 281 Bytes Settings for text generation tasks. Uploaded
merges.txt 1.82 MB Tokenizer merges for byte-pair encoding (BPE). Uploaded
model-00001-of-00004.safetensors 4.88 GB First part of model weights (split for LFS). Uploaded (LFS)
model-00002-of-00004.safetensors 4.93 GB Second part of model weights. Uploaded (LFS)
model-00003-of-00004.safetensors 4.33 GB Third part of model weights. Uploaded (LFS)
model-00004-of-00004.safetensors 1.09 GB Fourth part of model weights. Uploaded (LFS)
model.safetensors.index.json 29.5 kB Index file for managing model shards. Uploaded
special_tokens_map.json 644 Bytes Maps special tokens like <pad> or <eos>. Uploaded
tokenizer.json 11.4 MB Pre-trained tokenizer file in JSON format. Uploaded (LFS)
tokenizer_config.json 7.73 kB Configuration details for the tokenizer. Uploaded
vocab.json 2.78 MB Tokenizer vocabulary. Uploaded

Sample Long CoT:

Screenshot 2024-12-13 211732.png


Key Features:

  1. Model Size:

    • 7.62B parameters (FP16 precision).
  2. Model Sharding:

    • The model weights are split into 4 shards (safetensors) for efficient storage and download:
      • model-00001-of-00004.safetensors (4.88 GB)
      • model-00002-of-00004.safetensors (4.93 GB)
      • model-00003-of-00004.safetensors (4.33 GB)
      • model-00004-of-00004.safetensors (1.09 GB)
  3. Tokenizer:

    • Byte-pair encoding (BPE) based.
    • Files included:
      • vocab.json (2.78 MB)
      • merges.txt (1.82 MB)
      • tokenizer.json (11.4 MB)
    • Special tokens mapped in special_tokens_map.json (e.g., <pad>, <eos>).
  4. Configuration Files:

    • config.json: Defines model architecture and hyperparameters.
    • generation_config.json: Settings for inference and text generation tasks.

Training Dataset:


Use Cases:

  1. Instruction Following:
    Handle user instructions effectively, even for multi-step tasks.

  2. Reasoning Tasks:
    Perform logical reasoning and generate detailed step-by-step solutions.

  3. Text Generation:
    Generate coherent, context-aware responses.