Title: Hello HN!<p>I&#x27;ve been thinking about the idea of a LLM thats a clone of me - instead of generating replies to be a helpful assistant, it generates replies that are exactly like mine. The concept&#x27;s appeared in fiction numerous times (the talking paintings in Harry Potter that mimic the person painted, the clones in The Prestige), and I think with LLMs, there might actually be a possibility of us doing something like this!<p>I&#x27;ve just released a fork of the facebookresearch&#x2F;llama-recipes which allows you to fine-tune a Llama model on your personal WhatsApp conversations. This adaptation can train the model (using QLoRA) to respond in a way that&#x27;s eerily similar to your own texting style.<p>What I&#x27;ve figured out so far:<p>Quick Learning: The model quickly adapts to personal nuances, emoji usage, and phrases that you use. I&#x27;ve trained just 1 epoch on a P100 GPU using QLoRA and 4 bit quantization, and its already captured my mannerisms<p>Turing Tests: As an experiment, I asked my friends to ask me 3 questions, and responded with 2 candidate responses (one from me and one from llama). My friends then had to guess which candidate response was mine and which one was Llama&#x27;s. Llama managed to fool 10% of my friends, but with more compute, I think it can do way better.<p>Here&#x27;s the GitHub repository: <a href="https:&#x2F;&#x2F;github.com&#x2F;Ads-cmu&#x2F;WhatsApp-Llama&#x2F;">https:&#x2F;&#x2F;github.com&#x2F;Ads-cmu&#x2F;WhatsApp-Llama&#x2F;</a><p>Would love to hear feedback, suggestions, and any cool experiences if you decide to give it a try! I&#x27;d love to see how far we can push this by training bigger models for more epochs (I ran out of compute credits)
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