dree25/llama-3.2-3b-sft-model-1
dree25/llama-3.2-3b-sft-model-1 is a 3.2 billion parameter Llama model developed by dree25, fine-tuned from unsloth/llama-3.2-3b-unsloth-bnb-4bit. This model was trained 2x faster using Unsloth and Huggingface's TRL library, offering a context length of 32768 tokens. It is designed for efficient performance due to its optimized training process.
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Model Overview
dree25/llama-3.2-3b-sft-model-1 is a 3.2 billion parameter Llama model, developed by dree25. It is fine-tuned from the unsloth/llama-3.2-3b-unsloth-bnb-4bit base model, leveraging the Unsloth library and Huggingface's TRL for accelerated training.
Key Characteristics
- Architecture: Llama 3.2
- Parameter Count: 3.2 billion
- Context Length: 32768 tokens
- Training Efficiency: Trained 2x faster using Unsloth and Huggingface's TRL library, indicating an optimization for speed during the fine-tuning process.
Intended Use
This model is suitable for applications where a compact yet capable Llama-based model is required, especially benefiting from its efficient training methodology. Its 3.2 billion parameters make it a good candidate for tasks requiring a balance between performance and resource consumption.