hmdmahdavi/s1-generator-critique-Qwen3-4B-Instruct-2507-20251214_200751
This model is a 4 billion parameter instruction-tuned language model, fine-tuned by hmdmahdavi from the Qwen3-4B-Instruct-2507 base model. With a context length of 40960 tokens, it is optimized for generating critiques and responses to open-ended questions. It leverages SFT training via TRL to enhance its conversational and generative capabilities.
Loading preview...
Model Overview
This model, s1-generator-critique-Qwen3-4B-Instruct-2507-20251214_200751, is a specialized 4 billion parameter instruction-tuned language model. It is a fine-tuned variant of the Qwen3-4B-Instruct-2507 base model, developed by hmdmahdavi. The model was trained using the TRL library with a Supervised Fine-Tuning (SFT) approach.
Key Capabilities
- Instruction Following: Designed to respond effectively to user instructions, particularly for generating critiques or detailed answers.
- Conversational Generation: Optimized for producing coherent and contextually relevant text in response to open-ended questions.
- Extended Context: Benefits from the base model's 40960-token context length, allowing for processing and generating longer, more complex interactions.
Training Details
The model's training procedure involved Supervised Fine-Tuning (SFT) to adapt its responses to specific generative tasks. The training process utilized TRL version 0.12.0, Transformers 4.57.3, Pytorch 2.5.1, Datasets 4.4.1, and Tokenizers 0.22.1.
Good For
- Generating detailed critiques or analyses.
- Answering complex, open-ended questions requiring nuanced responses.
- Applications where a fine-tuned conversational model with a large context window is beneficial.