sambhav24045/deepseek-r1-rpsc-1stgrade
The sambhav24045/deepseek-r1-rpsc-1stgrade is a 7.6 billion parameter Qwen2 model, fine-tuned by sambhav24045 from unsloth/DeepSeek-R1-Distill-Qwen-7B-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. With a 32768 token context length, it is optimized for tasks benefiting from efficient fine-tuning and the Qwen2 architecture.
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Model Overview
The sambhav24045/deepseek-r1-rpsc-1stgrade is a 7.6 billion parameter Qwen2-based language model, developed by sambhav24045. It was fine-tuned from the unsloth/DeepSeek-R1-Distill-Qwen-7B-bnb-4bit model, leveraging the Unsloth library in conjunction with Huggingface's TRL library. This combination enabled a reported 2x faster training process for this specific fine-tuned iteration.
Key Characteristics
- Architecture: Based on the Qwen2 model family.
- Parameter Count: 7.6 billion parameters.
- Training Efficiency: Utilizes Unsloth for accelerated fine-tuning.
- Context Length: Supports a substantial context window of 32768 tokens.
Potential Use Cases
This model is suitable for applications requiring a Qwen2-based model that has undergone efficient fine-tuning. Its substantial context length makes it potentially useful for tasks involving longer inputs or requiring extensive contextual understanding. Developers looking for a model fine-tuned with Unsloth's speed benefits might find this particularly relevant.