Semantic search web app using the Large Language Model (LLM) Cohere for embeddings to match context and meaning, rather than keywords.
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Published by primaryobjects 4 months ago
Efficient vector DB on large datasets from disk, using minimal memory.
Efficient vector database for hundred millions of embeddings.
An AI monster generator web app using the Large Language Model (LLM) Cohere with the EntityFramew...
A repository to demonstrate some of the concepts behind large language models, transformer (found...
Multilingual Semantic Search with Reranking on a prepared large vectorized dataset comprising 10 ...
A demonstration of how a toy (but usable!) semantic search engine can be quickly built using Cohe...
Code examples and jupyter notebooks for the Cohere Platform
Cohere and Weaviate powered ThruThink support chat on Streamlit
A simple NPM interface for seamlessly interacting with 36 Large Language Model (LLM) providers, i...
A sandbox repo for grounded question answering with Cohere and Google Search
Public demos using the Cohere platform!
A NodeJS RAG framework to easily work with LLMs and embeddings
Vector search demo with the arXiv paper dataset, RedisVL, HuggingFace, OpenAI, Cohere, FastAPI, R...
Create chatbots with ease
A demonstration of a multilingual semantic search engine you can be quickly built using Cohere's ...