Open-Source AI Cookbook
The Open-Source AI Cookbook is a collection of notebooks illustrating practical aspects of building AI applications and solving various machine learning tasks using open-source tools and models.
Latest notebooks
Check out the recently added notebooks:
- Have several agents collaborate in a multi-agent hierarchy 🤖🤝🤖
- Semantic reranking with Elasticsearch
- Benchmarking TGI
- Generate a Preference Dataset with distilabel
- Clean an Existing Preference Dataset with LLMs as Judges
- Building RAG with Custom Unstructured Data
- Agentic RAG: turbocharge your RAG with query reformulation and self-query! 🚀
- Create a Transformers Agent from any LLM inference provider
- Fine-tuning LLM to Generate Persian Product Catalogs in JSON Format
- Agent for text-to-SQL with automatic error correction
- Information Extraction with Haystack and NuExtract
- RAG with Hugging Face and Milvus
- Data analyst agent: get your data’s insights in the blink of an eye ✨
- Enhancing RAG Reasoning with Knowledge Graphs
- Fine-Tuning Object Detection on a Custom Dataset 🖼, Deployment in Spaces, and Gradio API Integration
- Fine-Tuning a Semantic Segmentation Model on a Custom Dataset and Usage via the Inference API
You can also check out the notebooks in the cookbook’s GitHub repo.
Contributing
The Open-Source AI Cookbook is a community effort, and we welcome contributions from everyone! Check out the cookbook’s Contribution guide to learn how you can add your “recipe”.
< > Update on GitHub