With Ray AI Runtime, fine-tuning #LLMs is a breeze By enabling simple scaling of workloads, workflows, and frameworks, Ray AI Runtime simplifies the ecosystem of ML frameworks, platforms, and tools. Check out these use cases https://
bit.ly/496kBdD
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Ray AI Runtime Simplifies LLM Fine-Tuning at Scale
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Building Research Assistants with Swappable Retrievers
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Building a research assistant (long form YouTube tutorial) Starts by building a web research assistant, but covers how to swap in an arbitrary retriever. Uses an Arxiv retriever… what retriever would you want to swap in?
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Data Science Interview Questions and Answers Curated Guide
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GitHub – youssefHosni/Data-Science-Interview-Questions-Answers: Curated list of data science interview questions and answers https://
bit.ly/42FHnF3 #AI #MachineLearning #DeepLearning #LLMs #DataScience -
NVIDIA Releases Makani Library for AI Weather Climate Modeling
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I am so excited to see that the long-planned release of the Makani library https://
github.com/NVIDIA/makani for #AI based weather and climate modeling has finally happened! It started with our FourCastNet work almost three years ago using the Fourier neural operator, where we showed for -
Data Wrangling Functions for Education Research
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Cghlewis/data-wrangling-functions: Functions used for wrangling education research data https://
bit.ly/3PKAzTo #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Integrate LLaMa Chatbot with WhatsApp Using Official Tutorial
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Want to hook up your own LLaMa chatbot to Whatsapp? There's plenty of tutorials out there, but there's now an official tutorial + sample code: https://
github.com/facebookresear
ch/llama-recipes/blob/main/demo_apps/whatsapp_llama2.md#building-a-llama-enabled-whatsapp-chatbot
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OpenAI Assistants API feedback improvements documentation
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If you have tried the new @OpenAI Assistants API, what can we improve? Are there things that are not clear from the docs? Please drop questions / feedback in this thread
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OpenAI RAG Strategies for Improving Application Performance
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Applying OpenAI's RAG strategies At demo day, OpenAI reported a series of useful tricks for improving RAG app performance. In this short guide, we:
1/ Describe each of the strategies mentioned 2/ Link to docs so you can test each for yourself
3/ Show related ideas that -
Interactive Ridge Regression Tutorial and Numerical Demonstrations
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PythonNumericalDemos/Interactive_Ridge_Regresion.ipynb at master · GeostatsGuy/PythonNumericalDemos https://
bit.ly/3QcL3JY #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Self-Query Template: Leveraging Metadata in RAG Systems
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Self Query Template (
@elastic
) Often times documents come with really useful metadata! But how can you best take advantage of this metadata when doing RAG? Self-query is one way to do so. This converts a natural language query into one piece that is embedded and