Fine-Tuning Llama-2: A Comprehensive Case Study for Tailoring Custom Models
Just to add to this, I run through a lot of these topics around fine-tuning Llama 2 on your own dataset (for me it's my own code :P) in a coding live stream a couple weeks ago. All on Colab single GPU<p>Fine-tuning Llama stream: <a href="https://www.youtube.com/watch?v=TYgtG2Th6fI&t=2282s">https://www.youtube.com/watch?v=TYgtG2Th6fI&t=2282s</a><p>I have a couple more one where I do a QLoRa fine tuning session and explain the concepts as a personally self taught engineer (software engineer of 8 years moving into ML recently)<p>QloRa fine-tuning stream: <a href="https://www.youtube.com/watch?v=LitybCiLhSc&t=4584s">https://www.youtube.com/watch?v=LitybCiLhSc&t=4584s</a><p>Overall I'm trying to breakdown how I'm approaching a lot of my personal projects and my current AI driven startup. Want to make this information as accessible as possible. Also have a series where I'm fine-tuning a model to be the smallest webdev llm as possible which seems like people are liking. Only been streaming for about a month and plenty more to come.<p>Ask me any question about the stream and fine-tuning llama!