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1
- Introduction
2
- Text Tutorial on MLExpert.io
3
- Falcon LLM
4
- Google Colab Setup
5
- Dataset
6
- Load Falcon 7b and QLoRA Adapter
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- Try the Model Before Training
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- HuggingFace Dataset
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- Training
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- Save the Trained Model
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- Load the Trained Model
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- Evaluation
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- Conclusion
Description:
Learn how to fine-tune the Falcon 7b Large Language Model on a custom dataset of chatbot customer support FAQs using QLoRA. Explore the process of loading the model, implementing a LoRA adapter, and conducting fine-tuning. Monitor training progress with TensorBoard and compare the performance of untrained and trained models by evaluating responses to various prompts. Gain insights into working with free-to-use LLMs for research and commercial purposes, and discover techniques for adapting powerful language models to specific tasks using limited computational resources.

Fine-Tuning LLM with QLoRA on Single GPU - Training Falcon-7b on ChatBot Support FAQ Dataset

Venelin Valkov
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#Computer Science #Artificial Intelligence #Natural Language Processing (NLP) #LLM (Large Language Model) #Machine Learning #Deep Learning #Stable Diffusion #LoRA (Low-Rank Adaptation) #Model Evaluation #TensorFlow #Tensorboard #QLoRA
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- Introduction