zypchn/BehChat-qwen-SFT-v1
The zypchn/BehChat-qwen-SFT-v1 is a 7.6 billion parameter Qwen2-based causal language model developed by zypchn, fine-tuned from unsloth/deepseek-r1-distill-qwen-7b-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language generation tasks, leveraging its Qwen2 architecture and 32768 token context length for robust performance.
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Model Overview
zypchn/BehChat-qwen-SFT-v1 is a 7.6 billion parameter language model based on the Qwen2 architecture, developed by zypchn. It was fine-tuned from the unsloth/deepseek-r1-distill-qwen-7b-unsloth-bnb-4bit model, utilizing the Unsloth library for accelerated training and Huggingface's TRL library for the fine-tuning process. This approach allowed for a reported 2x faster training speed.
Key Characteristics
- Base Model: Qwen2 architecture
- Parameter Count: 7.6 billion parameters
- Context Length: 32768 tokens
- Training Method: Fine-tuned using Unsloth and Huggingface's TRL library, emphasizing efficient training.
- License: Apache-2.0
Potential Use Cases
This model is suitable for a variety of general-purpose language generation and understanding tasks, benefiting from its Qwen2 foundation and substantial context window. Its efficient training methodology suggests a focus on practical deployment and performance.