Hyeongwon/P2-split4_prob_Qwen3-8B-Base_0325-01
Hyeongwon/P2-split4_prob_Qwen3-8B-Base_0325-01 is an 8 billion parameter language model, fine-tuned from ChuGyouk/Qwen3-8B-Base using the TRL library. This model has undergone Supervised Fine-Tuning (SFT) and is designed for general text generation tasks, leveraging a 32K token context window. It is suitable for applications requiring nuanced conversational responses or creative text outputs.
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Model Overview
Hyeongwon/P2-split4_prob_Qwen3-8B-Base_0325-01 is an 8 billion parameter language model, fine-tuned from the ChuGyouk/Qwen3-8B-Base architecture. This model was developed using the TRL library and specifically trained with Supervised Fine-Tuning (SFT) techniques.
Key Characteristics
- Base Model: Fine-tuned from ChuGyouk/Qwen3-8B-Base.
- Training Method: Utilizes Supervised Fine-Tuning (SFT).
- Context Length: Supports a context window of 32,768 tokens.
- Frameworks: Developed with TRL (0.25.1), Transformers (4.57.3), Pytorch (2.6.0), Datasets (3.6.0), and Tokenizers (0.22.2).
Intended Use Cases
This model is suitable for a variety of text generation tasks, particularly those benefiting from its fine-tuned nature. Developers can integrate it using the Hugging Face transformers pipeline for applications such as:
- Generating conversational responses.
- Creative writing and content generation.
- Answering open-ended questions, as demonstrated in the quick start example.
Further details on the training process and metrics can be explored via the associated Weights & Biases run.