Cre4T3Tiv3/unsloth-llama3-alpaca-lora
Advanced 4-bit QLoRA fine-tuning pipeline for LLaMA 3 8B with production-grade optimization. Memory-efficient training on consumer GPUs for instruction-following specialization. Demonstrates cutting-edge parameter-efficient fine-tuning with Unsloth integration.
This project helps AI developers and machine learning engineers create specialized large language models (LLMs) without needing super expensive hardware. You input an existing LLaMA 3 8B model and your custom instruction dataset, and it outputs a fine-tuned model adapter, ready for deployment. This allows you to tailor a general-purpose LLM to perform specific tasks or follow particular instructions more accurately.
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Use this if you are an AI developer or machine learning engineer looking to fine-tune a LLaMA 3 8B model efficiently on consumer-grade GPUs to create a custom instruction-following LLM.
Not ideal if you need a production-ready model for highly critical domains or factual QA, or if your application requires handling contexts longer than 2K tokens.
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Apache-2.0
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Last pushed
Jul 11, 2025
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