TTahir/Llama3bv1
TTahir/Llama3bv1 is a 3.2 billion parameter Llama-based instruction-tuned language model developed by TTahir. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is designed for general instruction-following tasks, leveraging its efficient training methodology for practical applications.
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Model Overview
TTahir/Llama3bv1 is a 3.2 billion parameter instruction-tuned language model built upon the Llama architecture. Developed by TTahir, this model distinguishes itself through its efficient training process, utilizing Unsloth and Huggingface's TRL library, which reportedly enabled a 2x speedup in fine-tuning.
Key Characteristics
- Architecture: Llama-based, specifically fine-tuned from
unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit. - Parameter Count: 3.2 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: Leverages Unsloth for accelerated fine-tuning, making it a potentially faster option for deployment and iteration.
- Context Length: Supports a context window of 32768 tokens.
Use Cases
This model is suitable for a variety of general instruction-following tasks where a compact yet capable language model is required. Its efficient training background suggests it could be a good candidate for applications prioritizing faster development cycles or resource-constrained environments.