Скачать с ютуб Make LLM Fine Tuning 5x Faster with Unsloth в хорошем качестве

Make LLM Fine Tuning 5x Faster with Unsloth

In this tutorial, I've shared an exciting method to speed up your large language model (LLM) fine-tuning process using "Unsloth." Unsloth is a breakthrough library designed to work seamlessly with HuggingFace, enhancing the efficiency of LLM fine-tuning on NVIDIA GPUs. This video is a comprehensive guide on how to leverage Unsloth for fine-tuning different architectures, including "Llama" and "Mistral," using the TRL trainers (SFTTrainer, DPOTrainer, PPOTrainer). Key Highlights: 1. Introduction to Unsloth: Discover what makes Unsloth a game-changer in the world of LLM fine-tuning. 2. Optimized Operations: Learn how Unsloth overwrites standard modeling code with highly optimized operations. 3. Efficiency & Accuracy: Understand how Unsloth manages to reduce memory usage and accelerate fine-tuning, all while maintaining a 0% accuracy loss compared to regular QLoRA. 4. Practical Demonstration: Watch as I fine-tune a Mistral 7B LLM (4bit) on the IMDB dataset for text generation, all within Google Colab using Unsloth. Whether you're a beginner or an experienced practitioner, this tutorial is designed to provide you with the knowledge and tools to fine-tune LLMs more efficiently. Remember, if you find this content helpful, please hit that Like button, and consider subscribing to the channel for more tutorials like this. Your support means a lot! Also, feel free to drop any questions or feedback in the comments section below. Happy fine-tuning, and I'll see you in the next tutorial! Code: https://github.com/AIAnytime/Unsloth-... Unsloth: https://github.com/unslothai/unsloth Join this channel to get access to perks:    / @aianytime   #ai #generativeai #llm