Llama 2 is the first open-source language model of the same caliber as OpenAI’s models, and because it’s open source you can hack it to do new things that aren’t possible with GPT-4.
Like become a better poet. Talk like Homer Simpson. Write Midjourney prompts. Or replace your best friends.
A stampede of futuristic llamas by ai-forever/kandinsky-2.2
One of the main reasons to fine-tune models is so you can use a small model do a task that would normally require a large model. This means you can do the same task, but cheaper and faster. For example, the 7 billion parameter Llama 2 model is not good at summarizing text, but we can teach it how.
In this guide, we’ll show you how to create a text summarizer. We’ll be using Llama 2 7B, an open-source large language model from Meta and fine-tuning it on a dataset of messenger-like conversations with summaries. When we’re done, you’ll be able to distill chat transcripts, emails, webpages, and other documents into a brief summary. Short and sweet.
