I'm begging you @OpenAIDevs
, please tell us how your chunking works! It's a small detail, but it makes a huge difference in helping me make decisions about how to effectively use your RAG implement
LLMS
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OpenAI Chunking Strategy for RAG Implementation Details
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AirChat Gaining Popularity with TIES-Merging Explanation
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ai airchat is popping. i asked for an explanation of TIES-merging (ft @maximelabonne
’s model merging guide) and @nisten obliged: https://
air.chat/nisten/post/82
887bb6-5f2f-4c8e-9941-a6bb625f1282?thread_id=17843165-f817-3f7b-84f0-14476b6cd8f6
… airchat is basically twitter remade in @naval
’s image, but one benefit is that you cant write in pompous corpo language, -
Cheapest GPU Server Options for Running Mixtral Models
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What's the cheapest option right now for me to spin up a Linux server somewhere for an hour with enough GPU to run the latest Mixtral model?
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Fine-tuning Strategy: Sequential Layer Training Approach
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Has anyone tried fine-tuning half of the layers in one run, and then the other half in another? cc @teknium @winglian @erhartford
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Snowflake Arctic Embed Open Source Models Launch
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Snowflake Arctic Embed Yesterday @SnowflakeDB shipped their open source Arctic family of embedding models. You can use them with our @huggingface Embeddings connector to use these exceptionally performant models locally. Python docs: https://
python.langchain.com/docs/integrati
ons/providers/snowflake/#embedding-models
… Snowflake -
OpenAI Updates Kill Startups While RAG Becomes Standard
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Every OpenAI product update kills a bunch of startups & expensive consulting projects. RAG is increasingly being built into core AI model offerings (but RAG is quite limited, and, at times, risky. See halfway though this post: https://
oneusefulthing.org/p/which-ai-sho
uld-i-use-superpowers
…) -
Assistants API Updates: Expanded File Support and Better Control
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Launching a series of updates to the Assistants API—now with support for up to 10,000 files for knowledge retrieval and more precise tool and token control. Excited to see what you build!
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Optimize Multiple LLM Calls by Mixing Models for Lower Latency
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Most LLM apps and AI Agents need multiple calls to an LLM, especially a moderately complex LLM app/AI agent. Calling GPT-4 or Claude is impractical and you will soon be in high-latency hell. The optimal way to do this is to mix and match LLMs depending on the latency,
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LangSmith Evaluations: Unit Tests for LLM Development
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LangSmith Evaluations: Unit Tests
— LangChain (@LangChain) 17 avril 2024
Evaluations can accelerate LLM app development, but it can be challenging to get started. We've kicked off a new video series focused on evaluations in LangSmith.
This is the 10th video in our series that shows how to incorporate unit… pic.twitter.com/nSd8CiuAdRLangSmith Evaluations: Unit Tests Evaluations can accelerate LLM app development, but it can be challenging to get started. We've kicked off a new video series focused on evaluations in LangSmith. This is the 10th video in our series that shows how to incorporate unit
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RAG Fundamentals Tutorial Free on FreeCodeCamp
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RAG From Scratch on FreeCodeCamp We recently released a playlist of videos that explain RAG fundamentals and highlights over a dozen advanced RAG papers / methods. This tutorial is now free on @freeCodeCamp
! Thanks @beaucarnes and team. Video: https://
youtube.com/watch?v=sVcwVQ
RHIc8
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