gjyotin305/Llama-3.2-3B-Instruct_old_sft_alpaca_007
The gjyotin305/Llama-3.2-3B-Instruct_old_sft_alpaca_007 is a 3.2 billion parameter instruction-tuned Llama model developed by gjyotin305. It was finetuned from unsloth/Llama-3.2-3B-Instruct 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.
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Model Overview
The gjyotin305/Llama-3.2-3B-Instruct_old_sft_alpaca_007 is an instruction-tuned language model with 3.2 billion parameters, developed by gjyotin305. It is based on the Llama architecture, specifically finetuned from the unsloth/Llama-3.2-3B-Instruct base model.
Key Characteristics
- Efficient Training: This model was trained significantly faster, achieving a 2x speedup, by utilizing the Unsloth library in conjunction with Huggingface's TRL (Transformer Reinforcement Learning) library.
- Instruction-Tuned: As an instruction-tuned model, it is optimized to follow user prompts and instructions effectively, making it suitable for a variety of conversational and task-oriented applications.
- Apache 2.0 License: The model is released under the permissive Apache 2.0 license, allowing for broad use and distribution.
Potential Use Cases
This model is well-suited for applications requiring a compact yet capable instruction-following LLM, particularly where training efficiency was a key factor in its development. Its 3.2 billion parameters make it a good candidate for deployment in environments with moderate computational resources.