Explore >> Select a destination
|
You are here 
|
blog.pythonanywhere.com | ||
| | | | |
bdtechtalks.com
|
|
| | | | | Retrieval augmented generation (RAG) enables you to use custom documents with LLMs to improve their precision. | |
| | | | |
simonwillison.net
|
|
| | | | | Embeddings are a really neat trick that often come wrapped in a pile of intimidating jargon. If you can make it through that jargon, they unlock powerful and exciting techniques ... | |
| | | | |
www.shakudo.io
|
|
| | | | | A step-by-step guide to chat with your PDFs and extract information using open-source LLMs on Shakudo. | |
| | | | |
www.ai21.com
|
|
| | | By grounding AI in an organization's unique expertise, Retrieval-Augmented Generation (RAG) helps enterprises overcome hurdles in deploying large language models. AI21's RAG Engine provides advanced retrieval capabilities without enterprises having to invest heavily in development and maintenance. | ||
