Full text tutorial (requires MLExpert Pro): [ Ссылка ]
Getting bad predictions from your Tiny LLM? Learn how to fine-tune a small LLM (e.g. Phi-2, TinyLlama) and (possibly) increase your model's performance. You'll understand how to set up a dataset, model, tokenizer, and LoRA adapter. We'll train the model (Tiny Llama) on a single GPU with custom data and evaluate the predictions.
AI Bootcamp (in preview): [ Ссылка ]
Discord: [ Ссылка ]
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GitHub repository: [ Ссылка ]
00:00 - Intro
00:36 - Text tutorial on MLExpert
01:01 - Why fine-tuning Tiny LLM?
04:38 - Prepare the dataset
09:46 - Model & tokenizer setup
11:32 - Token counts
12:41 - Fine-tuning with LoRA
22:13 - Training results & saving the model
24:00 - Inference with the trained model
28:05 - Evaluation
30:46 - Conclusion
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#artificialintelligence #sentimentanalysis #llm #llama2 #chatgpt #gpt4 #python #chatbot
