BRlkl/distill-sft-qwen3-8b-full
BRlkl/distill-sft-qwen3-8b-full is an 8 billion parameter language model, fine-tuned from unsloth/Qwen3-8B using the TRL framework. This model is specifically trained with Supervised Fine-Tuning (SFT) to enhance its conversational and generative capabilities. With a 32K context length, it is designed for general text generation tasks, particularly excelling in interactive question-answering scenarios.
Loading preview...
Model Overview
BRlkl/distill-sft-qwen3-8b-full is an 8 billion parameter language model, derived from the unsloth/Qwen3-8B base model. It has undergone Supervised Fine-Tuning (SFT) using the TRL (Transformer Reinforcement Learning) framework, specifically version 0.24.0. This fine-tuning process aims to optimize the model's performance for conversational and text generation tasks.
Key Capabilities
- General Text Generation: Capable of generating coherent and contextually relevant text based on user prompts.
- Conversational AI: Enhanced for interactive dialogues and question-answering, as demonstrated by its quick start example.
- 32K Context Length: Supports processing longer inputs and generating more extensive responses, allowing for deeper contextual understanding.
Training Details
The model's training procedure utilized SFT, leveraging TRL for efficient fine-tuning. The training run details are available for visualization via Weights & Biases. The development environment included Transformers 4.57.6, Pytorch 2.9.1, Datasets 4.3.0, and Tokenizers 0.22.2.
Good For
- Developers seeking a Qwen3-8B variant optimized for instruction-following and conversational applications.
- Applications requiring robust text generation with a substantial context window.
- Experimentation with SFT-tuned models for various NLP tasks.