Fine tune Gemma 3, Qwen3, Llama 4, Phi 4 and Mistral Small with Unsloth and Transformers скачать в хорошем качестве

Fine tune Gemma 3, Qwen3, Llama 4, Phi 4 and Mistral Small with Unsloth and Transformers

📜Get repo access at https://Trelis.com/ADVANCED-fine-tuning 🗝️ Get Trelis Multi-Repo Bundle (https://Trelis.com/multi-repo-bundle) Access all SEVEN Trelis Github Repos (-robotics, -vision, -evals, -fine-tuning, -inference, -voice, -time-series) Support via Github Issues & Trelis’ Private Discord Tip: If you subscribe here on YouTube, click the bell to be notified of new vids 💡 Done-for-you Custom Fine-tuning Services Learn More: https://trelis.com/fine-tuning-services/ 💸 Starting a New Project/Venture? Apply for a Trelis Grant: https://trelis.com/trelis-ai-grants/ 📧 Get Trelis AI Tutorials by Email Subscribe on Substack: https://trelis.substack.com Video Links: slides: https://docs.google.com/presentation/... unsloth GitHub: https://github.com/unslothai/unsloth TIMESTAMPS: 0:00 Fine-tune Gemma Llama Qwen Phi Mistral 0:27 Video Overview 1:35 When to do fine-tuning? 3:22 How to prepare a fine-tuning dataset? 6:24 Choosing unsloth versus transformers 11:07 How to run fast evaluations with vLLM 12:33 What model to fine-tune? 14:27 General fine-tuning tips 16:04 Fine-tuning notebooks and setup: trelis.com/advanced-fine-tuning 19:11 Running fast evaluations with vLLM in a jupyter notebook 37:56 Fine-tuning with Unsloth 1:09:02 Fine-tuning with transformers 1:20:24 Conclusion