Fine-Tuning Llama 3 on a Custom Dataset: Training LLM for a RAG Q&A Use Case on a Single GPU
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- เผยแพร่เมื่อ 8 ก.ค. 2024
- Are you happy with your Large Language Model (LLM) performance on a specific task? If not, fine-tuning might be the answer. Even a simpler, smaller model can outperform a larger one if it's fine-tuned correctly for a specific task. In this video, you'll learn how to fine-tune Llama 3 on a custom dataset.
Model on HF: huggingface.co/curiousily/Lla...
Philipp Schmid Post: www.philschmid.de/fine-tune-l...
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00:00 - Why fine-tuning?
00:25 - Text tutorial on MLExpert.io
00:53 - Fine-tuning process overview
02:19 - Dataset
02:56 - Lllama 3 8B Instruct
03:53 - Google Colab Setup
05:30 - Loading model and tokenizer
08:18 - Create custom dataset
14:30 - Establish baseline
17:37 - Training on completions
19:04 - LoRA setup
22:25 - Training
26:42 - Load model and push to HuggingFace hub
28:43 - Evaluation (comparing vs the base model)
32:50 - Conclusion
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#llama3 #llm #rag #finetuning #promptengineering #chatgpt #chatbot #langchain #gpt4
Full-text tutorial (requires MLExpert Pro): www.mlexpert.io/bootcamp/fine-tuning-llama-3-llm-for-rag
What performance did you get with your fine-tuned model?
How to buy monthly subscription please let me know any link for it? As the link says yearly need the link for monthly
Great stuff as usual. Very useful info!
Im looking for this ❣️
Can we fine tune to 2bit model ?