Mistral + Haystack Collection: build RAG pipelines that rock 🤘
Collection of notebooks and resources to build Retrieval Augmented Generation pipelines using:
💻 For other great Haystack Notebooks, check out the 👩🏻🍳 Haystack Cookbook
| Model | Haystack version | Link | Details | Author |
|---|---|---|---|---|
| Mistral-7B-Instruct-v0.1 | 1.x | 🎸 Notebook | RAG on a collection of Rock music resources, using the free Hugging Face Inference API | @anakin87 |
| Mixtral-8x7B-Instruct-v0.1 | 1.x | 📄🚀 Notebook | RAG on a PDF File, using the free Hugging Face Inference API (using the free Hugging Face Inference API) | @AlessandroDiLauro |
| Mixtral-8x7B-Instruct-v0.1 | 1.x | 🛒 Notebook 📊🔍 Blog post |
RAG from CSV, Product description analysis | @AlessandroDiLauro |
| Mixtral-8x7B-Instruct-v0.1 | 2.x | 🕸️💬 Notebook | RAG on the Web, using the free Hugging Face Inference API | @TuanaCelik |
| Zephyr-7B Beta | 2.x | 🪁 Article and notebook | Article on how make this great model (fine-tuned from Mistral) run locally on Colab | @TuanaCelik @anakin87 |
| Mixtral-8x7B-Instruct-v0.1 | 2.x | 🩺💬 Article and notebook | Healthcare chatbot with Mixtral, Haystack, and PubMed | @annthurium |
| Mixtral-8x7B-Instruct-v0.1 | 2.x | 🇮🇹🇬🇧🎧 Notebook | Multilingual RAG from a podcast | @anakin87 |
| Mixtral-8x7B-Instruct-v0.1 | 2.x | 📰 Notebook | Building a Hacker News Top Stories TL;DR | @TuanaCelik |
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Great and deep blog post by Hugging Face on the MoE architecture, which is the basis of Mistral 8x7B.
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Zephyr: Direct Distillation of LM Alignment
Technical report by the Hugging Face H4 team. They explain how they trained Zephyr, a strong 7B model fine-tuned from Mistral.
The main topic is: ⚗️ how to effectively distill the capabilities of GPT-4 into smaller models? The report is insightful and well worth reading. I have summarized it here.