armbues/SiLLM-examples
Examples for using the SiLLM framework for training and running Large Language Models (LLMs) on Apple Silicon
This collection provides practical examples for fine-tuning and evaluating large language models (LLMs) specifically on Apple Silicon hardware. It helps developers and researchers experiment with different training methods like LoRA and DPO, and benchmark model performance. You can use various datasets and pre-trained models, and the output includes trained models or evaluation metrics like perplexity and MMLU scores.
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Use this if you are an AI/ML developer or researcher working with large language models on Apple Silicon and need hands-on examples for training, fine-tuning, or benchmarking model performance.
Not ideal if you are an end-user looking for a ready-to-use application, or if you are not working with Apple Silicon hardware.
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Python
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MIT
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Last pushed
May 08, 2025
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