Jonathan Xue

Whenever you come across a noteworthy announcement (blog post, paper) of a new dataset/model, tag @EcosystemGraphs and an LM agent will create a GitHub PR that we will review and merge into the Ecosystem Graphs, which tracks the latest foundation models: youtu.be/F0CExdM4ftA

@NielsRogge @huggingface @Apple @hkust @EcosystemGraphs

Depth estimation is a quickly evolving field in computer vision! 2 recent releases on @huggingface: - DepthPro by @Apple (Transformer-based): huggingface.co/papers/2410.02… - Lotus by @hkust (Diffusion-based): huggingface.co/papers/2409.18…

@OfficialLoganK @EcosystemGraphs

Say hello to Gemini 1.5 Flash-8B ⚡️, now available for production usage with: - 50% lower price (vs 1.5 Flash) - 2x higher rate limits (vs 1.5 Flash) - lower latency on small prompts (vs 1.5 Flash) developers.googleblog.com/en/gemini-15-f…

@EcosystemGraphs @EcosystemGraphs

@mattshumer_ @huggingface @hyperbolic_labs @EcosystemGraphs

The weights of our 70B model are available today on @huggingface here: huggingface.co/mattshumer/Ref… @hyperbolic_labs API available later today. Next week, we will release the weights of Reflection-405B, along with a short report going into more detail on our process and findings.

I'm excited to announce Reflection 70B, the world’s top open-source model. Trained using Reflection-Tuning, a technique developed to enable LLMs to fix their own mistakes. 405B coming next week - we expect it to be the best model in the world. Built w/ @GlaiveAI. Read on ⬇️:

@AIatMeta @Arm @MediaTek @Qualcomm @EcosystemGraphs

📣 Introducing Llama 3.2: Lightweight models for edge devices, vision models and more! What’s new? • Llama 3.2 1B & 3B models deliver state-of-the-art capabilities for their class for several on-device use cases — with support for @Arm, @MediaTek & @Qualcomm on day one. • Llama 3.2 11B & 90B vision models deliver performance competitive with leading closed models — and can be used as drop-in replacements for Llama 3.1 8B & 70B. • New Llama Guard models to support multimodal use cases and edge deployments. • The first official distro of Llama Stack simplifies and supercharges the way developers & enterprises can build around Llama to support agentic applications and more. Details in the full announcement ➡️ go.fb.me/229ug4 Download Llama 3.2 models ➡️ go.fb.me/w63yfd These models are available to download now directly from Meta and @HuggingFace — and will be available across offerings from 25+ partners that are rolling out starting today, including @accenture, @awscloud, @AMD, @azure, @Databricks, @Dell, @Deloitte, @FireworksAI_HQ, @GoogleCloud, @GroqInc, @IBMwatsonx, @Infosys, @Intel, @kaggle, @NVIDIA, @OracleCloud, @PwC, @scale_AI, @snowflakeDB, @togethercompute and more. With Llama 3.2 we’re making it possible to run Llama in even more places, with even more flexible capabilities. We’ve said it before and we’ll say it again: open source AI is how we ensure that these innovations reflect the global community they’re built for and benefit everyone. We’re continuing our drive to make open source the standard with Llama 3.2.

@MistralAI @EcosystemGraphs

mistral.ai/news/pixtral-1… 2/2

mistral.ai/news/september… 1/2

@acostin @Adobe @EcosystemGraphs

Welcome to the world, @Adobe Firefly Video model (announced today, public beta later this year)! Designed to be safe for commercial use, for great cinematic quality and fluid motion, camera controls and of course, deep integration into our tools. The labor of love of a team dedicated to help creative professionals ideate and edit video. I can't wait to see what the community will do with it later this year! blog.adobe.com/en/publish/202… #AdobeFirefly @creativecloud.

@googledevs @EcosystemGraphs

Introducing DataGemma, open models that enhance LLM factuality by grounding them with real-world data from Data Commons → goo.gle/4gooxdG Learn how the models use RIG & RAG approaches to: 📖 Harness Data Commons knowledge 🧠 Fact-check numbers 🛠️ Develop responsible AI

@Alibaba_Qwen @EcosystemGraphs

Welcome to the party of Qwen2.5 foundation models! This time, we have the biggest release ever in the history of Qwen. In brief, we have: Blog: qwenlm.github.io/blog/qwen2.5/ Blog (LLM): qwenlm.github.io/blog/qwen2.5-l… Blog (Coder): qwenlm.github.io/blog/qwen2.5-c… Blog (Math): qwenlm.github.io/blog/qwen2.5-m… HF Collection: huggingface.co/collections/Qw… ModelScope: modelscope.cn/organization/q… HF Demo: huggingface.co/spaces/Qwen/Qw… * Qwen2.5: 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B * Qwen2.5-Coder: 1.5B, 7B, and 32B on the way * Qwen2.5-Math: 1.5B, 7B, and 72B. All our open-source models, except for the 3B and 72B variants, are licensed under Apache 2.0. You can find the license files in the respective Hugging Face repositories. Furthermore, we have also open-sourced the **Qwen2-VL-72B**, which features performance enhancements compared to last month's release. As usual, we not only opensource the bf16 checkpoints but we also provide quantized model checkpoints, e.g, GPTQ, AWQ, and GGUF, and thus this time we have a total of over 100 model variants! Notably, our flagship opensource LLM, Qwen2.5-72B-Instruct, achieves competitive performance against the proprietary models and outcompetes most opensource models in a number of benchmark evaluations! We heard your voice about your need of the welcomed 14B and 32B models and so we bring them to you. These two models even demonstrate competitive or superior performance against the predecessor Qwen2-72B-Instruct! SLM we care as well! The compact 3B model has grasped a wide range of knowledge and now is able to achive 68 on MMLU, beating Qwen1.5-14B! Besides the general language models, we still focus on upgrading our expert models. Still remmeber CodeQwen1.5 and wait for CodeQwen2? This time we have new models called Qwen2.5-Coder with two variants of 1.5B and 7B parameters. Both demonstrate very competitive performance against much larger code LLMs or general LLMs! Last month we released our first math model Qwen2-Math, and this time we have built Qwen2.5-Math on the base language models of Qwen2.5 and continued our research in reasoning, including CoT, and Tool Integrated Reasoning. What's more, this model now supports both English and Chinese! Qwen2.5-Math is way much better than Qwen2-Math and it might be your best choice of math LLM! Lastly, if you are satisfied with our Qwen2-VL-72B but find it hard to use, now you got no worries! It is OPENSOURCED! Prepare to start a journey of innovation with our lineup of models! We hope you enjoy them!

@Muennighoff @EcosystemsGraph

Releasing OLMoE - the first good Mixture-of-Experts LLM that's 100% open-source - 1B active, 7B total params for 5T tokens - Best small LLM & matches more costly ones like Gemma, Llama - Open Model/Data/Code/Logs + lots of analysis & experiments 📜arxiv.org/abs/2409.02060 🧵1/9

@AIatMeta @Eco_Graphs_Bot

Introducing Meta Segment Anything Model 2 (SAM 2) — the first unified model for real-time, promptable object segmentation in images & videos. SAM 2 is available today under Apache 2.0 so that anyone can use it to build their own experiences Details ➡️ go.fb.me/p749s5