tbf writing is my least favorite part of this job but my year-long quest to build a local bot (explicitly not an API) that can successfully do this part of my job for me has thus far not been successful
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Building Optimized LLM Inference Systems Efficiently
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Learn how to build an optimized LLM inference system from the ground up in our new short course, Efficiently Serving LLMs, built in collaboration with @predibase and taught by @TravisAddair.
— Andrew Ng (@AndrewYNg) 18 mars 2024
Whether you're serving your own LLM or using a model hosting service, this course will… pic.twitter.com/tyCVsi4SKXLearn how to build an optimized LLM inference system from the ground up in our new short course, Efficiently Serving LLMs, built in collaboration with @predibase and taught by @TravisAddair
. Whether you're serving your own LLM or using a model hosting service, this course will -
European Digital Education Event Keynote on Code and Innovation
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I was really honored to be the keynote at this prestigious European event. Enjoy! https://
youtu.be/i1ExZ2Bo9I0?si
=9LLQl-5Mqs2pd5G4
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#digitaleu #eucodeweek #teachday #innovation #technology #education #edutech @ArturHabant @elaniaz @DigitalEU @Khulood_Almani @stratorob @SpirosMargaris @HaroldSinnott -
DeepLearningAI Course on Efficiently Serving LLMs Launched
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Excited to share the launch of the @DeepLearningAI course Efficiently Serving #LLMs developed w/ @predibase CTO @TravisAddair Implement a modern inference stack w/ caching, batching & #quantization Intro to #LoRA adapters
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RAG Query Routing: Handling Multiple Datastores
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RAG From Scratch: Routing Our RAG From Scratch video series walks through impt RAG concepts in short / focused videos w/ code. This is the 10th video in our series and focuses on query routing. Problem: We often have multiple possible datastores (e.g., different vectorDBs,
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RAG Complexity: Query Understanding and Document Retrieval Challenges
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RAG is difficult to get right because the system has to understand your query before retrieving the appropriate documents from the vector store. It’s a complex machine-learning problem and you have to solve for multiple parts: query re-writing, efficient retrieval, re-ranking,
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Hugging Face Adds Granular Repository Access Control for Organizations
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This feature has been requested for the longest time You can now define granular access control to repositories inside your organization on HF. (This is a Enterprise Hub feature ) Is this useful to you?
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Voyage AI Embedding Integration Package for LangChain
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@Voyage_AI_ Embedding Integration Package Use the same custom embeddings that power Chat LangChain via the new langchain-voyageai package! Recommended by @AnthropicAI as their preferred embedding provider, Voyage AI builds custom embedding models for your company or
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EuroPython 2024 CFP Review: Python, AI, Data Engineering Tracks
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Will be reviewing CFPs at @europython 2024 I have chosen these 4 tracks: – Python and Community – PyData: AI and LLMs – PyData: Data Engineering – Python Libraries and Tooling
