Keras has a MLX backend in progress. I'd like to work with a few folks who are part of both the MLX community & the Keras community to get it over the finish line. If you're interested — please send me an email!
OPEN SOURCE
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TMLR Paper with Experiments, Data and Code Resources
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More experiments can be found in our TMLR paper: https://
arxiv.org/abs/2310.14540
Data and code: https://
huggingface.co/datasets/yyama
da/SpatialEvalLLM
…, https://
github.com/runopti/Spatia
lEvalLLM
…
Special thanks to @AndrewLampinen for helpful discussion and advice!
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Open Source Library Seeking Evaluation Support
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I do actually have an open source library that needs evals right now – and it's open source (or will be) so no need to hide anything – I'll message you
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Building Custom Datasets for DSPy: Overcoming Documentation Gaps
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The getting started documentation currently uses an existing dataset – dspy.datasets.gsm8k – but that skips the most intimidating part of the closes which is figuring out how to build a dataset for my own problem https://
dspy-docs.vercel.app/docs/quick-sta
rt/minimal-example
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Using DSPy Without Building Evaluations: A Learning Curve Challenge
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Can you use DSPy without building evals? Because building evals is an enormous learning curve for most people (myself included)
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Data AI Summit Early Bird Registration Discount Ends April 30
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Early bird catches the worm Save $400 by registering for #DataAISummit before April 30! You’ll explore the latest advances in #ApacheSpark, Delta Lake, MLflow, LangChain, PyTorch, dbt, and more: https://
bit.ly/3UlaDA7 -
CodeGemma: Open Code LLM Family Matching Performance Benchmarks
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3/ CodeGemma – a family of open code LLMs based on Gemma; CodeGemma 7B models excel in mathematical reasoning and match the code capabilities of other open models.
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PyTorch Performance Improvements with Nightly Build and Optimizations
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THE REVENGE OF PYTORCH
just kidding 🙂 @cHHillee (from PyTorch team) was kindly able to help improve the PyTorch baseline, done by 1) upgrading to nightly, 2) using the "compound" F.sdpa (scaled dot product attention) layer directly, and turning on a torch compile flag: -
Testing LLM Clients: httpx and pytest-httpx Best Practices
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Plus I like to write tests for my code, and figuring out how to serve a mock HTTP response to each different LLM client library in turn is a whole lot more work than just using httpx and pytest-httpx – which I already know
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Testing LLM Client Libraries with httpx and pytest-httpx
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Plus I like to write tests for my code, and figuring out how to serve a mock HTTP response to each different LLM client library in turn is a whole lot more work than just using httpx and pytest-httpx – which I already know