Hyeongwon/PH_prob_mini_Qwen3-8B-Base_0305-01
PH_prob_mini_Qwen3-8B-Base_0305-01 is an 8 billion parameter language model developed by Hyeongwon, fine-tuned from ChuGyouk/Qwen3-8B-Base. This model was trained using Supervised Fine-Tuning (SFT) with the TRL framework, offering a 32768 token context length. It is designed for general text generation tasks, building upon the Qwen3 architecture.
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Model Overview
PH_prob_mini_Qwen3-8B-Base_0305-01 is an 8 billion parameter language model developed by Hyeongwon. It is a fine-tuned version of the ChuGyouk/Qwen3-8B-Base model, leveraging the Qwen3 architecture. The model was trained using Supervised Fine-Tuning (SFT) with the TRL framework, indicating a focus on instruction-following or specific task performance.
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on provided prompts.
- Instruction Following: Fine-tuned with SFT, suggesting improved performance on instruction-based tasks.
- Large Context Window: Supports a context length of 32768 tokens, allowing for processing and generating longer sequences of text.
Training Details
The model's training procedure involved Supervised Fine-Tuning (SFT) using the TRL library. The development utilized specific versions of key frameworks:
- TRL: 0.25.1
- Transformers: 4.57.3
- Pytorch: 2.6.0
- Datasets: 3.6.0
- Tokenizers: 0.22.2
Good For
- General-purpose text generation tasks.
- Applications requiring a model with a substantial context window.
- Further fine-tuning for specialized downstream applications.