we're willing to fix it to work better with uv (which is fantastic) cc: @_seemethere I think PyTorch was forced to solve the accelerator support problem before Python packaging was ready for it, so we solved it as best as we can — but we're willing to move to a better world if
TOOLS
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Groq API Chatbot Implementation with Gradio
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groq + gradio 🔥
— AK (@_akhaliq) 30 octobre 2024
chatbot using groq api in a few lines of code https://t.co/lGEC7enpzf pic.twitter.com/LPD0YfZBcjgroq + gradio chatbot using groq api in a few lines of code
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CodeGPT AI Reaches 1.4M Downloads Across 180 Countries
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Since launching in March of last year, @codegptAI has been downloaded over 1.4M times with users in 180+ countries. It's one of the top players in the AI for developers space and Llama models have been a big part of that. https://
go.fb.me/e0m38k -
Customize SLMs for GenAI Production at ODSC Conference
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Bay Area Friends: Are you headed to the Open Data Science Conference (ODSC) tomorrow in Burlingame? Don't miss this talk from ML Eng Lead, @grg_arnav to learn how to easily customize your own #SLMs and put into production for #GenAI applications at scale! Talk details:
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SambaNova Cloud Enables Fast Llama 3.2 AI Inferencing
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If we could dress up as SambaNova Cloud for #Halloween, we would 😎
— SambaNova (@SambaNovaAI) 30 octobre 2024
Take advantage of fast #AI inferencing on @AIatMeta's Llama 3.2, where you can build a cool new AI, or just use it figure out how to win "Best Costume" in your office party 🎃If we could dress up as SambaNova Cloud for #Halloween, we would Take advantage of fast #AI inferencing on @AIatMeta
's Llama 3.2, where you can build a cool new AI, or just use it figure out how to win "Best Costume" in your office party -
MiniOmni 2 Development and Production Pipeline Improvements
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Mostly hoping for MiniOmni 2 and likes to get better before putting time into production pipelines for them
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AI-Powered Architecture Diagram Generator Using Mistral and Qdrant
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An interesting use case – Architecture Diagram Generator
— FlowiseAI (@FlowiseAI) 30 octobre 2024
Developed using Flowise, Qdrant, and Mistral to enable translation of request into visual architecture diagramshttps://t.co/oYJ6JItUt5
shoutout to Mohamed Yasser for creating this! pic.twitter.com/hzSXeAtIgtAn interesting use case – Architecture Diagram Generator Developed using Flowise, Qdrant, and Mistral to enable translation of request into visual architecture diagrams https://
huggingface.co/spaces/yasserr
md/AWSArchitecture
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Simple Philosophy: Two Tools for Model Problem-Solving
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Our philosophy was to keep it simple. We gave the model just two tools: a Bash Tool for running commands and an Edit Tool for viewing/editing files. Then we let the model decide how to tackle each problem.
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SWE-bench Verified: AI Testing on Real GitHub Issues
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What is SWE-bench Verified? It's a human-validated subset of problems from the SWE-bench benchmark that tests AI's ability to solve real GitHub issues from popular Python repos. The model needs to understand the codebase, modify it, and pass the original unit tests.
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Choosing TTS Engines for Lightweight GPU Hardware Deployment
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It depends on the hardware you choose to deploy the TTS engine. For lightweight GPUs I’d recommend using MeloTTS