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Fine-Tuning LLMs (Gemma, LLaMA, Mistral, etc.) A practical guide to fine-tuning various large language models using popular frameworks. Includes examples, scripts, and tips for efficient training on custom datasets.

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deep-div/Fine-Tuning-LLMs-and-VisionModels

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🧠 Fine-Tuning LLMs (Gemma, LLaMA, Mistral, and More)

Welcome to this curated repository showcasing the fine-tuning of various open-source large language models (LLMs) such as Gemma, LLaMA, Mistral, and others using Hugging Face Transformers, PEFT (LoRA/QLoRA), and other modern libraries.

This repo is designed for researchers, ML engineers, and enthusiasts looking to explore or build on top of custom fine-tuned LLMs.

🔧 Features

  • ✅ Fine-tuning with Hugging Face Trainer and PEFT (LoRA / QLoRA)
  • ✅ Dataset loading and preprocessing
  • ✅ Tokenization and model configuration
  • ✅ Evaluation with custom metrics
  • ✅ Easy-to-edit configs for reproducibility
  • ✅ Support for mixed precision (fp16, bf16)

🧠 Contributing

Got improvements, additional models, or tips? Contributions are welcome! Just open an issue or submit a pull request.

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Fine-Tuning LLMs (Gemma, LLaMA, Mistral, etc.) A practical guide to fine-tuning various large language models using popular frameworks. Includes examples, scripts, and tips for efficient training on custom datasets.

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