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Experience the seamless integration of Cohere models with Amazon Web Services (AWS) through the first release of Cohere-on-AWS notebooks. These notebooks offer best practices on prompting, tool integrations, and more for your GenAI projects.

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GenAI @ AWS | Making LLM go brrrr!!!

🥳 Super excited about the first release of Cohere-on-AWS! If you need guidance and best-pratices of using Cohere models in Amazon Web Services (AWS), look no further than this amazing repo. What do you get (for now)... 🕵️♀️ Exploring LangChain Retrieval Algorithms: super efficient use of Embed-english and Command models, alongside FAISS and ChromaDB, for RAG flows. 🧑🏫 Prompting Guide 101 For Cohere Command R and R+: This is your source for best in class prompting of Cammand models. 👩🔧 Tool Use with Cohere on Bedrock: Last but not least, Tool use with Bedrock's Converse API. BIG shout out to Breanne Warner, Niithiyn Vijeaswaran and Preston Tuggle for creating and collecting these amazing resources in a single repo. AFAIK, they are not done with it! More to come! What are you waiting for, go check it out! Github: https://lnkd.in/g-BAwMqx #GenAI #GenerativeAI #MachineLearning #RAG #AWS #Cohere #FoundationModels #Bedrock #LLM #DataScience

GitHub - aws-samples/Cohere-on-AWS

GitHub - aws-samples/Cohere-on-AWS

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