ChuGyouk/10-1 is an 8 billion parameter language model fine-tuned from ChuGyouk/Qwen3-8B-Base. Developed by ChuGyouk, this model was trained using the TRL framework with SFT. It features a 32768 token context length, making it suitable for tasks requiring extended conversational memory or processing longer texts. This model is designed for general text generation applications.
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Model Overview
ChuGyouk/10-1 is an 8 billion parameter language model, fine-tuned by ChuGyouk from its base model, ChuGyouk/Qwen3-8B-Base. The training process utilized the TRL (Transformer Reinforcement Learning) framework, specifically employing Supervised Fine-Tuning (SFT).
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on given prompts.
- Extended Context: Supports a context length of 32768 tokens, allowing for processing and generating longer sequences of text.
- Fine-tuned Performance: Benefits from SFT, which typically enhances performance on specific tasks or improves general instruction following compared to base models.
Training Details
The model was trained using the TRL framework (version 0.24.0) with Transformers (4.57.3), Pytorch (2.9.1), Datasets (4.3.0), and Tokenizers (0.22.2). The training procedure involved Supervised Fine-Tuning (SFT).
Good For
- General-purpose text generation tasks.
- Applications requiring a model with a substantial context window.
- Developers looking for a fine-tuned 8B parameter model for various NLP applications.