not-lain (Hafedh Hichri)

reacted to AdinaY's post with 🔥 5 days ago

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RWKV7-G1 0.1B 🔥 Pure RNN reasoning model released by RWKV

Model: BlinkDL/rwkv7-g1
paper: RWKV-7 "Goose" with Expressive Dynamic State Evolution (2503.14456)

✨ Apache2.0
✨ Supports 100+ languages
✨ 0.1 B runs smoothly on low power devices
✨ 0.4B/1.5B/2.9B are coming soon!!

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reacted to Jaward's post with 🚀 5 days ago

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2055

Nvidia brings blue (from starwars droids) to life 🤯, supercute with flawless dexterity and droid voice. It's the result of their colab research with Google DeepMind and Disney, revealed as part of their new opensource physics engine for robotics simulation: NEWTON - which enables robots to learn how to complete complex tasks with greater precision.

ReadMore: https://developer.nvidia.com/blog/announcing-newton-an-open-source-physics-engine-for-robotics-simulation?ncid=so-twit-820797-vt48

reacted to csabakecskemeti's post with 😎 5 days ago

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GTC new model announcement now from Nvidia
nvidia/Llama-3_3-Nemotron-Super-49B-v1

GGUFs:
DevQuasar/nvidia.Llama-3_3-Nemotron-Super-49B-v1-GGUF

Enjoy!

reacted to m-ric's post with 🤗 8 days ago

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smolagents now support vLLM! 🥳

As one of the most popular local inference solutions, the community had been asking us to integrate vLLM: after a heavy refactoring of our LLM classes, we've just released smolagents 1.11.0, with a brand new VLLMModel class.

Go try it and tell us what you think!

https://github.com/huggingface/smolagents/blob/45b2c86857b7f7657daaa74e4d17d347e9e2c4a4/src/smolagents/models.py#L497

replied to their post 11 days ago

Glad to be of help 🙌

reacted to clem's post with 🚀🤗 11 days ago

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We just crossed 1,500,000 public models on Hugging Face (and 500k spaces, 330k datasets, 50k papers). One new repository is created every 15 seconds. Congratulations all!

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reacted to BrigitteTousi's post with 🤗 12 days ago

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Regardless of X being down or not, so glad I can rely on HF Posts for AI news ❤️🤗

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posted an update 12 days ago

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🚀AraClip is now fully integrated with Hugging Face 🤗

AraClip is a specialized CLIP model that was created by @pain and optimized for Arabic text-image retrieval tasks🔥

🔗 Try it out 🔗
🤖 model: Arabic-Clip/araclip
🧩 Gradio demo: Arabic-Clip/Araclip-Simplified
🌐 website: https://arabic-clip.github.io/Arabic-CLIP/

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reacted to as-cle-bert's post with ❤️👍 14 days ago

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I just released a fully automated evaluation framework for your RAG applications!📈

GitHub 👉 https://github.com/AstraBert/diRAGnosis
PyPi 👉 https://pypi.org/project/diragnosis/

It's called 𝐝𝐢𝐑𝐀𝐆𝐧𝐨𝐬𝐢𝐬 and is a lightweight framework that helps you 𝗱𝗶𝗮𝗴𝗻𝗼𝘀𝗲 𝘁𝗵𝗲 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗼𝗳 𝗟𝗟𝗠𝘀 𝗮𝗻𝗱 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗺𝗼𝗱𝗲𝗹𝘀 𝗶𝗻 𝗥𝗔𝗚 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀.

You can launch it as an application locally (it's Docker-ready!🐋) or, if you want more flexibility, you can integrate it in your code as a python package📦

The workflow is simple:
🧠 You choose your favorite LLM provider and model (supported, for now, are Mistral AI, Groq, Anthropic, OpenAI and Cohere)
🧠 You pick the embedding models provider and the embedding model you prefer (supported, for now, are Mistral AI, Hugging Face, Cohere and OpenAI)
📄 You prepare and provide your documents
⚙️ Documents are ingested into a Qdrant vector database and transformed into a synthetic question dataset with the help of LlamaIndex
📊 The LLM is evaluated for the faithfulness and relevancy of its retrieval-augmented answer to the questions
📊 The embedding model is evaluated for hit rate and mean reciprocal ranking (MRR) of the retrieved documents

And the cool thing is that all of this is 𝗶𝗻𝘁𝘂𝗶𝘁𝗶𝘃𝗲 𝗮𝗻𝗱 𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲𝗹𝘆 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱: you plug it in, and it works!🔌⚡

Even cooler? This is all built on top of LlamaIndex and its integrations: no need for tons of dependencies or fancy workarounds🦙
And if you're a UI lover, Gradio and FastAPI are there to provide you a seamless backend-to-frontend experience🕶️

So now it's your turn: you can either get diRAGnosis from GitHub 👉 https://github.com/AstraBert/diRAGnosis
or just run a quick and painless:

uv pip install diragnosis

To get the package installed (lightning-fast) in your environment🏃‍♀️

Have fun and feel free to leave feedback and feature/integrations requests on GitHub issues✨

reacted to Bils's post with 🚀 15 days ago

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Spatial sound experience! SonicOrbit features AI beat detection to auto-sync your rhythm.

Bils/SonicOrbit

reacted to daavoo's post with 👍 16 days ago

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Hi there 👋! Check this project for mapping features in OpenStreetMap with Computer Vision:

⭐-> https://github.com/mozilla-ai/osm-ai-helper

And a live demo showing how to map new swimming pools 🏊:

🗺️ -> mozilla-ai/osm-ai-helper

reacted to DualityAI-RebekahBogdanoff's post with 🚀 16 days ago

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🚀 Duality is super excited to announce that our Kaggle competition is LIVE! Synthetic-to-Real Object Detection Challenge is LIVE! 🚦
Want to master AI training, learn industry-proven synthetic data workflows, and compete for public recognition and cash prizes?

👉 Join our Synthetic-to-Real Object Detection Challenge on Kaggle! https://www.kaggle.com/competitions/synthetic-2-real-object-detection-challenge/overview

Compete to build the top-performing model capable of detecting real-world objects—trained entirely on synthetic data. Master these industry-proven methods for faster, more targeted, and diverse dataset creation, and set yourself apart, unlocking today's most exciting AI opportunities.

Ready to test your skills?

🏆 The Challenge

Train an object detection model using synthetic images created with Falcon—Duality AI's cutting-edge digital twin simulation software—then evaluate your model on real-world imagery.

The Twist?
📈 Boost your model’s accuracy by creating and refining your own custom synthetic datasets using Falcon! Get access to the tools and double the data by following this link and creating a free account-
https://falcon.duality.ai/secure/documentation/ex-1-objdetection?sidebarMode=learn

Win Cash Prizes & Recognition
🔹 Earn cash and public shout-outs from the Duality AI accounts
Enhance Your Portfolio
🔹 Demonstrate your real-world AI and ML expertise in object detection to prospective employers and collaborators.
Expand Your Network
🔹 Engage, compete, and collaborate with fellow ML engineers, researchers, and students.

🚀 Put your skills to the test and join our Kaggle competition today: https://www.kaggle.com/competitions/synthetic-2-real-object-detection-challenge/overview

reacted to andito's post with 🔥🚀 19 days ago

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Extremely bullish on @CohereForAI 's Aya Vision (8B & 32B) - new SOTA open-weight VLMs

- 8B wins up to 81% of the time in its class, better than Gemini Flash
- 32B beats Llama 3.2 90B!
- Covers 23 languages, excels in image captioning, VQA & more
- Integrated on transformers from Day 0!

Efficient multimodal models are here to stay!!🔥
Check out their blog! https://huggingface.co/blog/aya-vision

reacted to lysandre's post with 🔥🚀❤️ about 1 month ago

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SmolVLM-2 and SigLIP-2 are now part of transformers in dedicated releases!

They're added on top of the v4.49.0 release, and can be installed from the following tags: v4.49.0-SmolVLM-2 and v4.49.0-SigLIP-2.

This marks a new beginning for the release process of transformers. For the past five years, we've been doing monthly releases featuring many models (v4.49.0, the latest release, features 9 new architectures).

Starting with SmolVLM-2 & SigLIP2, we'll now additionally release tags supporting new models on a stable branch. These models are therefore directly available for use by installing from the tag itself. These tags will continue to be updated with fixes applied to these models.

Going forward, continue expecting software releases following semantic versioning: v4.50.0 will have ~10 new architectures compared to v4.49.0, as well as a myriad of new features, improvements and bug fixes. Accompanying these software releases, we'll release tags offering brand new models as fast as possible, to make them accessible to all immediately.

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reacted to merve's post with 👍 about 1 month ago

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Google just released PaliGemma 2 Mix: new versatile instruction vision language models 🔥

> Three new models: 3B, 10B, 28B with res 224, 448 💙
> Can do vision language tasks with open-ended prompts, understand documents, and segment or detect anything 🤯

Read more https://huggingface.co/blog/paligemma2mix
Try the demo google/paligemma2-10b-mix
All models are here google/paligemma-2-mix-67ac6a251aaf3ee73679dcc4

Hafedh Hichri

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