Fine Tune GPT In FIVE MINUTES with RLHF! - "Perform 10x Better For My Use Case" - FREE COLAB 📓
In this video, I show you how to fine-tune LLaMA 2 (and other LLMs) for your specific use case. This allows your GPT model to perform much better for your business or personal use case. Give LLaMA detailed information that it doesn't already have, make it respond in a specific tone/personality, and much more.
In this tutorial, we will be using reinforcement learning with human feed back(rlhf) to train our model, where we will train our model to only generate positive response. This technique can be further finetuned to create a chatbot which will be free from violent speech and any user can use it.
In this video, I will show you how to build your own open-source CHATGPT without ever writing a single line of code. Fine-tuning the LLaMA-2 model can provide several benefits, including improved performance, cost savings, and customization.
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Free Google Colab for 4bit QLoRA fine-tuning of llama-2-7b model
Rise and Rejoice - Fine-tuning Llama 2 made easier with this Google Colab Tutorial
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👉0:00 Intro and Problem in business.
👉1:48 Choose Policy Model and Reward Model.
👉3:34 Going deeper to Code Policy Model.
👉6:30 Comparing the Result of RLHF Trained model and Normal Model.
✍️Learn and write the code along with me.
🙏The hand promises that if you subscribe to the channel and like this video, it will release more tutorial videos.
👐I look forward to seeing you in future videos
LINK :
Dataset: https://www.kaggle.com/datasets/laksh...
Policy Model: https://huggingface.co/lvwerra/gpt2-imdb
Reward Model: https://huggingface.co/lvwerra/distil...
Notebook: https://colab.research.google.com/dri...
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