ahmadhasan/deepseek-r1-sft
The ahmadhasan/deepseek-r1-sft is a 7.6 billion parameter Qwen2-based causal language model, fine-tuned by ahmadhasan. 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 for robust performance.
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Model Overview
The ahmadhasan/deepseek-r1-sft is a 7.6 billion parameter language model, fine-tuned by ahmadhasan. It is based on the Qwen2 architecture, specifically finetuned from unsloth/deepseek-r1-distill-qwen-7b-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Qwen2-based causal language model.
- Parameter Count: 7.6 billion parameters.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Context Length: Supports a context window of 32768 tokens.
Potential Use Cases
This model is suitable for a variety of natural language processing tasks, particularly those benefiting from its Qwen2 foundation and efficient fine-tuning. Its 7.6B parameter size makes it a capable option for applications requiring a balance between performance and computational resources.