qingy2024/LLaMa_3.2_3B_Catalysts
qingy2024/LLaMa_3.2_3B_Catalysts is a 3 billion parameter Llama-3.2-based instruction-tuned model developed by qingy2019. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is evaluated on the Open LLM Leaderboard, showing performance across various benchmarks including IFEval, BBH, and MMLU-PRO.
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Model Overview
qingy2024/LLaMa_3.2_3B_Catalysts is a 3 billion parameter language model developed by qingy2019. It is fine-tuned from the unsloth/Llama-3.2-3B-Instruct base model, leveraging the Unsloth library for accelerated training (2x faster) in conjunction with Huggingface's TRL library.
Key Capabilities & Performance
This model's performance is evaluated on the Open LLM Leaderboard, providing insights into its general capabilities. Notable benchmark results include:
- Avg. Score: 19.63
- IFEval (0-Shot): 49.92
- BBH (3-Shot): 21.35
- MATH Lvl 5 (4-Shot): 11.10
- GPQA (0-shot): 5.15
- MuSR (0-shot): 7.95
- MMLU-PRO (5-shot): 22.31
Training Details
The model was trained with Unsloth, a framework designed to speed up the fine-tuning process for large language models, making it an efficient choice for developers looking for Llama-3.2 based models with optimized training. The full evaluation details are available on the Hugging Face Open LLM Leaderboard dataset.