Hamel Husain @HamelHusain
Researcher focusing on LLMs: https://t.co/iVZDFdIQiE Previously, dev tools and infra for ML. Ex @Github, @Airbnb, @DataRobot. @fastdotai core contributor. hamel.dev Portland, OR Joined September 2012-
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First, figure out WHAT the product is, WHAT problem it solves, WHY people want to use it. Get some traction & usage data. Then, bring in ML folks who can help with HOW to measure & improve, based on the data. Doing it reversed is like building solutions to nonexistent problems.
First, figure out WHAT the product is, WHAT problem it solves, WHY people want to use it. Get some traction & usage data. Then, bring in ML folks who can help with HOW to measure & improve, based on the data. Doing it reversed is like building solutions to nonexistent problems.
And ML folks don’t just train models. They’re also bring rigor, data driven analysis, best practices of how to use data and work with non-deterministic output, how to build products based on the above, etc These are things that typical software engineers may not focus on.
And ML folks don’t just train models. They’re also bring rigor, data driven analysis, best practices of how to use data and work with non-deterministic output, how to build products based on the above, etc These are things that typical software engineers may not focus on.
After 25 years of working in the ML space I agree that many early stage companies (Series A-ish and earlier) shouldn’t be hiring MLEs However I think companies need a fractional MLE (.05) to help ensure the foundations get built properly for MLEs later on. Data Eng,…
After 25 years of working in the ML space I agree that many early stage companies (Series A-ish and earlier) shouldn’t be hiring MLEs However I think companies need a fractional MLE (.05) to help ensure the foundations get built properly for MLEs later on. Data Eng,…
Berkeley Function Calling Leaderboard: Introducing Consistent 8 X V100 with pay-as-you-go pricing for measuring costs and latency. In depth: We fix inconsistency in the cost and latency calculation for open-source models, which are now all calculated when serving the model with…
Berkeley Function Calling Leaderboard: Introducing Consistent 8 X V100 with pay-as-you-go pricing for measuring costs and latency. In depth: We fix inconsistency in the cost and latency calculation for open-source models, which are now all calculated when serving the model with…
I made pdftext, a small tool that extracts text like pymupdf, but with an Apache license (mupdf is AGPL). It can pull out blocks and lines or plain text. Find it here - github.com/VikParuchuri/p… .
Does anyone know which provider this is referencing?
Does anyone know which provider this is referencing?
The API product is your developer documentation. If you don’t treat the docs like a first class product, developers will choose to go elsewhere.
This is the prompt they are using for Llama-3 function calling (seems to work well even though it's not specifically fine tuned for that): github.com/ShishirPatil/g…
This is the prompt they are using for Llama-3 function calling (seems to work well even though it's not specifically fine tuned for that): github.com/ShishirPatil/g… https://t.co/lNetEc4f8Y
Our first Build with Claude contest was a success! We received tons of great submissions from @AnthropicAI devs. Here are the 5 winning projects (in no particular order)🧵
Jeremy is THE most talented infra/devops person I know. He’s created a specialized IDE + Copilot for DevOps : K8s, Cloud, etc - based on notebooks! It’s open source, accompanied by a blog that shows his thinking 👇
Jeremy is THE most talented infra/devops person I know. He’s created a specialized IDE + Copilot for DevOps : K8s, Cloud, etc - based on notebooks! It’s open source, accompanied by a blog that shows his thinking 👇
"Do stuff and then blog about it" remains one of the most underrated pieces of career advice
"Do stuff and then blog about it" remains one of the most underrated pieces of career advice
I'm up to 96k context for Llama 3 8B. Using PoSE, we did continued pre-training of the base model w 300M tokens to extend the context length to 64k. From there we increased the RoPE theta to further attempt to extend the context length. 🧵
Love this, just came up IRL and often true
Made a Colab to finetune Llama-3 8b Instruct 2x faster and use 68% less VRAM No endless generations, fixed llama.cpp GGUF conversions, supports 4x longer contexts - 11K vs 2.5K before Also have a 2x faster inference only notebook: colab.research.google.com/drive/1aqlNQi7… colab.research.google.com/drive/1XamvWYi…
LOVE how the Meta team went hard on explicitly describing the prompt template llama.meta.com/docs/model-car…
Cool tool by @HamelHusain (and a primer on why declarative job execution, like with @BacalhauProject is so critical, even against black box models like LLMs!) - Debugging AI With Adversarial Validation bit.ly/3xOWy52
Don’t blindly base your decision on which LLM to use on broken benchmarks like MMLU... If you are serious about choosing the right LLM for your use case, you NEED to create an eval of your own. Let’s talk about how you can make one 🧵 x.com/nearcyan/statu…
Don’t blindly base your decision on which LLM to use on broken benchmarks like MMLU... If you are serious about choosing the right LLM for your use case, you NEED to create an eval of your own. Let’s talk about how you can make one 🧵 x.com/nearcyan/statu…
Does anyone have a reference implementation of function calling on llama 3 + vllm + outlines Surely someone has an open example - its helpful to see how other people are doing it b/c there are lots of ways of accomplishing this
I don't know anything about music production but this is amazing - definitely worth playing this demo
I don't know anything about music production but this is amazing - definitely worth playing this demo
I'm impressed that Spotify's recsys doesn't completely get borked by long bouts of kids music
Sebastian Raschka @rasbt
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Jeremy Howard @jeremyphoward
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elvis @omarsar0
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vicki @vboykis
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Chris Albon @chrisalbon
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Radek Osmulski 🇺�.. @radekosmulski
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merve @mervenoyann
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Mark Tenenholtz @marktenenholtz
114K Followers 544 Following Head of AI @PredeloHQ. XGBoost peddler, transformer purveyor.
Jeremy Howard @jeremyphoward
222K Followers 5K Following 🇦🇺 Co-founder: @AnswerDotAI & @FastDotAI ; Hon Professor: @UQSchoolITEE ; Digital Fellow: @Stanford
vicki @vboykis
52K Followers 1K Following Born: USSR. Raised: USA. ML Eng @mozillaai Ex: @duosec @Tumblr, @automattic Nights: 👦 & 👧 working on some ✨ new vectors ✨
Chris Albon @chrisalbon
86K Followers 2K Following Director of Machine Learning at the Wikimedia Foundation. We host Wikipedia.
Radek Osmulski 🇺�.. @radekosmulski
25K Followers 554 Following Resources to take your Machine Learning skills to the next level 🧪 Senior Data Scientist, RecSys @NVIDIAAI 🏫 @fastdotai trained DL Eng 📝 https://t.co/By87iXx5Pu
Erik Bernhardsson @bernhardsson
38K Followers 3K Following Building @modal_labs when I'm not posting bangers about data and software. Previously built the music rec sys at Spotify and ran the eng team at Better.
merve @mervenoyann
56K Followers 4K Following open-sourceress at @huggingface 🧙🏻♀️ proud mediterrenean 🍋 I do TL;DR on ML papers sometimes. RTs != endorsements
abhishek @abhi1thakur
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Soumith Chintala @soumithchintala
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343K Followers 189 Following The AI community building the future. https://t.co/VkRPD0VKaZ #BlackLivesMatter #stopasianhate
clem 🤗 @ClementDelangue
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3K Followers 849 Following CS PhD @ UC Berkeley. Creator of Gorilla, GoEx, RAFT, OpenFunctions and Berkeley Function Calling Leaderboard. Previously researcher @GoogleAI @MSFTResearch
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Howe Wang @WangUWS
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DJ @DuaneJRich
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