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Together Cookbook

The Together Cookbook is a collection of code and guides designed to help developers build with open source models using Together AI. The best way to use the recipes is to copy code snippets and integrate them into your own projects!

Contributing

We welcome contributions to this repository! If you have a cookbook you'd like to add, please reach out to use the Discord or open a pull request!

Prerequisites

To make the most of the examples in this cookbook, you'll need a Together AI API key (sign up for free here).

While the code examples are primarily written in Python/JS, the concepts can be adapted to any programming language that supports interaction with the Together API.

Cookbooks

Cookbook	Description	Open
Long Context Finetuning For Repetition	Fine-tuning LLMs to repeat back words in long sequences.
Summarization Long Context Finetuning	Long context fine-tuning to improve summarization capabilities.
Conversation Finetuning	Fine-tuning LLMs on multi-step conversations.
MultiModal_RAG_with_Nvidia_Investor_Slide_Deck	Multimodal RAG using Nvidia investor slides
Summarization Evaluation	Summarizing and evaluating outputs with LLMs.
Open_Contextual_RAG	An implementation of Contextual Retrieval using open models.
PDF_to_Podcast	Generate a podcast from PDF content NotebookLM style!
Embedding_Visualization	Visualize vector embeddings
Knowledge_Graphs_with_Structured_Outputs	Get LLMs to generate knowledge graphs
Search_with_Reranking	Improve search results with rerankers
Semantic_Search	Implement vector search with embedding models
Structured_Text_Extraction_from_Images	Extract structured text from images
Text_RAG	Implement text-based Retrieval-Augmented Generation

Explore Further

Looking for more resources to enhance your experience with open source models? Check out these helpful links:

Additional Resources