EASILY Train Llama 3 and Upload to Ollama.com (Must Know)

Unlock the full potential of LLaMA 3.1 by learning how to fine-tune this powerful AI model using your own custom data! 🚀 In this video, we’ll take you through a step-by-step guide to train LLaMA 3.1, save it on Hugging Face, and Olama. Perfect for businesses looking to leverage AI with their private data! 🌟 Massed compute: https://bit.ly/mervin-praison Coupon: MervinPraison (50% Discount) 🔍 What You’ll Learn: • Why fine-tuning is essential for custom data 📊 • Training the 8 billion parameter LLaMA 3.1 model 🦙 • How to save and deploy your model on Hugging Face and Olama 🌐 🔧 Steps Covered: 1. Configuration setup and data formatting ⚙️ 2. Pre-training model evaluation 📉 3. Data loading and training with SFT Trainer 📥 4. Post-training model evaluation and saving 🚀 5. Uploading the model to Hugging Face & Olama 🛠️ 💡 Benefits: • Custom AI model tailored to your specific needs 🎯 • Easy deployment and accessibility on various platforms 🌍 • Enhanced performance with less memory usage 💾 🔗 Links: Patreon: https://patreon.com/MervinPraison Ko-fi: https://ko-fi.com/mervinpraison Discord: https://discord.gg/nNZu5gGT59 Twitter / X : https://twitter.com/mervinpraison GPU for 50% of it's cost: https://bit.ly/mervin-praison Coupon: MervinPraison (50% Discount) Code: https://mer.vin/2024/07/llama-3-1-fine-tune/ 0:00 - Introduction to LLaMA 3.1 fine-tuning 1:07 - Overview of the video content 2:29 - Configuration 4:52 - Loading the dataset 6:40 - Training the model 8:12 - Saving the model 9:13 - Running the code and observing results 10:16 - Saving the model to Ollama 10:36 - Creating GGUF format 11:34 - Creating Ollama Modelfile 12:32 - Creating the model in Ollama 12:57 - Testing the model with Ollama 13:22 - Pushing the model to Ollama 14:17 - Final steps and conclusion