Get started with Gemma Google's NEW open-source LLM model
Channel: Prince Canuma
Date: 24/02/2024

In this video, I'll show you how to summarize large PDF documents locally on your laptop using Gemma 2B and 7B instruct models.

 ⚙️ Essential Tools We'll Be Using:

- MLX-LM: A library based on MLX, which is a framework for Machine learning research on your laptop or in a data center - by Apple.
- Huggingface: The Hugging Face Hub is a platform with over 120k models, 20k datasets, and 50k demos in which people can easily collaborate in their ML workflows.
- Langchain: LangChain is a framework for developing applications powered by language models.

🌟 What is Google Gemma?

Gemma is a family of lightweight, state-of-the-art open-source models built from the same research and technology used to create the Gemini models. 
Gemma comes in two sizes: Gemma 2B and Gemma 7B. Each size is released with pre-trained and instruction-tuned variants you can download using the links below.

🔗 Is Google Gemma free? 

Yes, Gemma is completely open-source and you can access it through Huggingface hub or Kaggle.

🤗 Download Model weights:
- Quantized for MLX: https://huggingface.co/collections/mlx-community/googles-gemma-65d9b6d041325e422e9cb8bb
- Full precision: https://huggingface.co/collections/google/gemma-release-65d5efbccdbb8c4202ec078b

📘 Additional Resources:

- Colab Notebook: https://colab.research.google.com/github/Blaizzy/LLMOps/blob/main/inference/local/mlx/Summarization.ipynb
- Github Repo: https://github.com/Blaizzy/LLMOps/tree/main/inference/local/mlx

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