Shishir Patil @shishirpatil_
CS PhD @ UC Berkeley. Creator of Gorilla, GoEx, RAFT, OpenFunctions and Berkeley Function Calling Leaderboard. Previously researcher @GoogleAI @MSFTResearch shishirpatil.github.io Berkeley, CA Joined July 2009-
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[1/5] Introducing Stylus 🖌️ - an #AI tool that automatically finds and adds the best adapters (LoRAs, Textual Inversions, Hypernetworks) to #StableDiffusion based on your prompt. 🗞️ Paper: arxiv.org/abs/2404.18928 🌎 Project Page: stylus-diffusion.github.io
@Dave_Ideate I'd say there are two big problems (a) LLMs can't provide any guarantees on their internal state and therefore a programmer cannot put bounds on correctness for state management. This has led to great work by @shishirpatil_ and team on GoEx. (b) RAG doesn't extend reasoning…
Excited to welcome Snowflake-Arctic on the Berkeley Function Calling Leaderboard ❄️ How does Snowflake-arctic-instruct, an apache-2.0 licensed, 480B parameter MoE model perform on invoking functions (aka tools)? Attached is a quick comparison with gpt-4-0125-preview (yellow).…
Important point
Under-appreciated leaderboard in my opinion - function calling (aka tool usage) is one of the most interesting applications of LLMs, plus it should be independent of how much "knowledge" is baked into the models
Under-appreciated leaderboard in my opinion - function calling (aka tool usage) is one of the most interesting applications of LLMs, plus it should be independent of how much "knowledge" is baked into the models
Check out how good is Llama 3 on tool calling 👀 Thorough work by @RickLamers on the Berkeley Tool Calling Leaderboard!
Check out how good is Llama 3 on tool calling 👀 Thorough work by @RickLamers on the Berkeley Tool Calling Leaderboard!
GoEX: Perspectives and Designs Towards a Runtime for Autonomous LLM Applications arxiv.org/html/2404.0692… by Shishir G. Patil et al (UC Berkeley) and @martin_casado (a16z) This is a super interesting paper with the underlying thesis that “post-facto LLM validation” is a better…
🤩 Looking good 🦍👌😂
Hey @burkov, Thanks for featuring our work! We want to point out that our evaluation does not only measure the function choice accuracy; we do take into account the correct choice of parameters and their values. What’s more, in our Leaderboard April 1st release, we patched it to…
Hey @burkov, Thanks for featuring our work! We want to point out that our evaluation does not only measure the function choice accuracy; we do take into account the correct choice of parameters and their values. What’s more, in our Leaderboard April 1st release, we patched it to…
📢 Berkeley Function-Calling Leaderboard is amazing! It evaluates the LLM's ability to call functions (aka tools) accurately. There are proprietary and open models! I see Hermes 2 Pro ranking 20th 👀 Now I have to try Gorilla OpenFunctions v2! Thanks @shishirpatil_ and…
How to do better RAG? 🤔Check out in this webinar with @jerryjliu0 on the shortcoming of today's RAG 👀and how a few simple tricks to create a fine-tuning data-set can vastly improve performance for in-domain RAG! And thanks to @ravithejads RAFT is now already part of…
How to do better RAG? 🤔Check out in this webinar with @jerryjliu0 on the shortcoming of today's RAG 👀and how a few simple tricks to create a fine-tuning data-set can vastly improve performance for in-domain RAG! And thanks to @ravithejads RAFT is now already part of…
Thanks for sharing our work @arankomatsuzaki 🫡
Thanks for sharing our work @arankomatsuzaki 🫡
How are LoRAs and longer contexts for LLMs related? Check out @xiuyu_l and @sijun_tan's latest work on training LoRA adapters to support in-domain long-context 🗞️
How are LoRAs and longer contexts for LLMs related? Check out @xiuyu_l and @sijun_tan's latest work on training LoRA adapters to support in-domain long-context 🗞️
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I'll be presenting the Neural Phishing Attack paper at #ICLR2024 next week, DM me if you want to chat! We'll be in "Halle B #220" at Thu 9 May 10:45 a.m. CEST (this is more for me to remember lol)
Fun, AI town coverage .... with a lot of good resources. ibtimes.co.uk/ai-town-simula…
@shishirpatil_ @luo_michael1234 @HelloCivitai @huggingface @brandontrabucco @bignamehyp @profjoeyg @rsalakhu Thanks @shishirpatil_ , we couldn't have done it without the #gorilla trailblazing S tier research!
[1/5] Introducing Stylus 🖌️ - an #AI tool that automatically finds and adds the best adapters (LoRAs, Textual Inversions, Hypernetworks) to #StableDiffusion based on your prompt. 🗞️ Paper: arxiv.org/abs/2404.18928 🌎 Project Page: stylus-diffusion.github.io
@Dave_Ideate I'd say there are two big problems (a) LLMs can't provide any guarantees on their internal state and therefore a programmer cannot put bounds on correctness for state management. This has led to great work by @shishirpatil_ and team on GoEx. (b) RAG doesn't extend reasoning…
Check out the latest Snowflake-Arctic's performance on the Berkeley Function Calling Leaderboard ❄️☃️
Excited to welcome Snowflake-Arctic on the Berkeley Function Calling Leaderboard ❄️ How does Snowflake-arctic-instruct, an apache-2.0 licensed, 480B parameter MoE model perform on invoking functions (aka tools)? Attached is a quick comparison with gpt-4-0125-preview (yellow).…
📢 [Berkeley Function Calling Leaderboard Update] Llama-3, Command-R-Plus, and Gemini-Pro-1.5 has been added to the family. We aim to provide a systematic, fair, and practical guide for the function calling capabilities of LLMs. Check out latency and costs at…
📊Delighted to welcome Command-R-Plus, Llama-3, and and Gemini-Pro-1.5 into the Berkeley Function Calling Leaderboard. Check out how they stack up across different categories, P95 latency, and costs at gorilla.cs.berkeley.edu/leaderboard.ht… Congratulations to @cohere, @AIatMeta, and…
Important point
This cost + latency for llama 3 is actually insane. Just look at the rest of the models in comparison
Under-appreciated leaderboard in my opinion - function calling (aka tool usage) is one of the most interesting applications of LLMs, plus it should be independent of how much "knowledge" is baked into the models
📊Delighted to welcome Command-R-Plus, Llama-3, and and Gemini-Pro-1.5 into the Berkeley Function Calling Leaderboard. Check out how they stack up across different categories, P95 latency, and costs at gorilla.cs.berkeley.edu/leaderboard.ht… Congratulations to @cohere, @AIatMeta, and…
Precisely 🫡
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…
After a grueling few days of having to click accept to view the chatbot leaderboard, we put it back on HF :p huggingface.co/spaces/lmsys/c…
🫡 Checkout Command-R-Plus, Llama-3, and Gemini-Pro-1.5 function calling performance on Berkeley Function-Calling Leaderboard! 🔥 Amazing performance from Llama3 70B in multiple test categories! Come checkout the detailed breakdown in gorilla.cs.berkeley.edu/leaderboard.ht…
📊Delighted to welcome Command-R-Plus, Llama-3, and and Gemini-Pro-1.5 into the Berkeley Function Calling Leaderboard. Check out how they stack up across different categories, P95 latency, and costs at gorilla.cs.berkeley.edu/leaderboard.ht… Congratulations to @cohere, @AIatMeta, and…
A few (maybe obvious) challenges using LLMs within software applications I've seen as companies roll out their use: - versioning : While it's possible to tie a program to a specific model version, there is no structured way to handle new model versions (e.g. deprecation, sub…
The reception from the Llama 3 community has been wild. We think of future generations of Llama not just as a model, but an e2e system. Our work on Torchtune and Purple Llama are 2 early artifacts in our journey to open the higher layers of abstraction. More on this soon!
Already almost 1,000 llama3 model variations have been shared publicly on HF (many more in private use at companies): huggingface.co/models?sort=cr…. Everyone should fine-tune their own models for their use-cases, languages, industry, infra constraints,... 10,000 llama3 variants by…
Frontier level Tool Calling now live on @GroqInc powered by Llama 3 🫡 Outperforms GPT-4 Turbo 2024-04-09 and Claude 3 Opus (FC version) in multiple subcategories At 300 tokens/s 🚀 I've personally been working on this feature, and man, the new Llama is good!
A fun backstory: we first demoed this breakthrough to @finkd, @Ahmad_Al_Dahle and others this February on a single node. There was so much excitement about this research that in a mere 2 months we scaled it up and today is in production available to billions via Meta AI #movefast
In addition to Llama 3, today we’re also publishing a new paper: Imagine Flash: Accelerating Emu Diffusion Models with Backward Distillation ➡️ go.fb.me/g4r584 This work from GenAI researchers is enabling new image generation features in Meta AI on @WhatsApp & web.
I was curious how Llama-3 performs on my favorite math problem 🧮 I first encountered the problem at @CanUSAMathcamp mathcamp.org/2006/quiz/.
🦙 We're excited to host @Meta Llama-3 8b and 70b on Anyscale Endpoints! ➕ Fine-tuning, JSON mode and function calling support coming soon as well! Pricing: - 8B: $0.15 / Million tokens - 70B: $1.00 / Million tokens
So very excited for the promotion of @JenniferHli to GP. She's a primary reason @a16z enterprise investing is what it is, being a key player behind so many deals, our team and our investment philosophy and process. She really is "the best of us". a16z.com/jennifer-li/
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