HoangCuongNguyen/qwen3-8b-safetysft
HoangCuongNguyen/qwen3-8b-safetysft is an 8 billion parameter language model fine-tuned from Qwen/Qwen3-8B-Base using Supervised Fine-Tuning (SFT) with the TRL framework. This model is designed for general text generation tasks, leveraging its base architecture for broad applicability. Its fine-tuning process aims to enhance its safety and response quality for conversational AI and content creation. The model offers a 32768 token context length, making it suitable for processing longer inputs and generating coherent, extended outputs.
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Model Overview
HoangCuongNguyen/qwen3-8b-safetysft is an 8 billion parameter language model derived from the Qwen/Qwen3-8B-Base architecture. This model has undergone Supervised Fine-Tuning (SFT) using the TRL (Transformers Reinforcement Learning) framework, indicating a focus on refining its conversational abilities and response quality. The fine-tuning process aims to improve the model's safety and alignment for various text generation applications.
Key Capabilities
- General Text Generation: Capable of generating human-like text for a wide range of prompts.
- Fine-tuned Responses: Benefits from SFT to produce more refined and contextually appropriate outputs.
- Extended Context Handling: Supports a substantial context length of 32768 tokens, allowing for processing and generating longer, more complex narratives or discussions.
Training Details
This model was trained using the SFT method within the TRL framework. The development utilized specific versions of key libraries:
- TRL: 1.0.0
- Transformers: 5.13.1
- Pytorch: 2.12.0+cu130
- Datasets: 5.0.0
- Tokenizers: 0.22.2
Use Cases
This model is suitable for applications requiring robust text generation, including chatbots, content creation, summarization, and question-answering systems where safety and quality of responses are important considerations.