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✨Just released: NVIDIA Nemotron post-training multi-lingual dataset ✨ We expanded permissive post-training dataset with addition of synthetically translated reasoning traces. ✋ Five new languages 💪 World class reasoning traces 🤗 Learn more: 📥 Download:

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13,800 görüntüleme • 10 ay önce •via X (Twitter)

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💚🤗💚 Jensen showing Hugging Face during GTC keynote, where NVIDIA AI dropped amazing new open models, datasets and blogs! Some of my favorites, links in comments: 🧠 Nemotron 3 Super 120A12B - Reasoning LLM 🏥 Open-H-Embodiment - Healthcare Robotics Dataset 🩻 Cosmos-H-Surgical-Simulator - World Foundation Model 🚕 Alpamayo 1.5 - Autonomous Vehicle Model and Datasets 🕺 Kimodo v1 - Generate body movement from prompts! And SO MUCH MORE to explore at
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💚🤗💚 Jensen showing Hugging Face during GTC keynote, where NVIDIA AI dropped amazing new open models, datasets and blogs! Some of my favorites, links in comments: 🧠 Nemotron 3 Super 120A12B - Reasoning LLM 🏥 Open-H-Embodiment - Healthcare Robotics Dataset 🩻 Cosmos-H-Surgical-Simulator - World Foundation Model 🚕 Alpamayo 1.5 - Autonomous Vehicle Model and Datasets 🕺 Kimodo v1 - Generate body movement from prompts! And SO MUCH MORE to explore at

Jeff Boudier 🤗

19,922 görüntüleme • 3 ay önce

Introducing Alpamayo 1.5. Based on community feedback, we’ve updated our 10B-parameter chain-of-thought reasoning VLA model to be a more interactive and steerable engine for autonomous vehicle development. Built on the Cosmos-Reason2 VLM backbone, this release adds support for navigation guidance and flexible camera configurations while providing new post-training scripts for model adaptation. 🤗 Learn more:
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Introducing Alpamayo 1.5. Based on community feedback, we’ve updated our 10B-parameter chain-of-thought reasoning VLA model to be a more interactive and steerable engine for autonomous vehicle development. Built on the Cosmos-Reason2 VLM backbone, this release adds support for navigation guidance and flexible camera configurations while providing new post-training scripts for model adaptation. 🤗 Learn more:

NVIDIA DRIVE

50,693 görüntüleme • 2 ay önce

NVIDIA Nemotron 3 Nano Omni, a new multimodal reasoning model, is now live on Jetson AI Lab and unifies vision, audio, and language into a single reasoning loop. 🙌 Power your NemoClaws by running this model with Ollama, vLLM and other inference frameworks on NVIDIA Jetson hardware. Try it ➡️
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NVIDIA Nemotron 3 Nano Omni, a new multimodal reasoning model, is now live on Jetson AI Lab and unifies vision, audio, and language into a single reasoning loop. 🙌 Power your NemoClaws by running this model with Ollama, vLLM and other inference frameworks on NVIDIA Jetson hardware. Try it ➡️

NVIDIA Robotics

15,828 görüntüleme • 1 ay önce

Google just released the AlphaEarth Foundations with 64 dimensions of satellite embeddings at 10-m resolution at the global scale! It is very interesting! Check it out Blog post: Dataset: Paper: #AI #geospatial #remotesensing #geoai
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Google just released the AlphaEarth Foundations with 64 dimensions of satellite embeddings at 10-m resolution at the global scale! It is very interesting! Check it out Blog post: Dataset: Paper: #AI #geospatial #remotesensing #geoai

Qiusheng Wu

47,026 görüntüleme • 10 ay önce

Today we’re releasing SAIR, the Structurally Augmented IC50 Repository. SAIR is the Largest Open-Sourced Binding Affinity Dataset with Cofolded 3D Structures. It includes more than 5 million protein-ligand structures, generated using our Large Quantitative Models and labeled with binding affinity data. By providing this unprecedented scale of structure-activity data, we aim to enable researchers to train and evaluate new AI models for drug discovery, bridging the historical gap between molecular structures and drug potency prediction. The SAIR dataset was created using the NVIDIA DGX Cloud and is now publicly available on the Google Cloud Platform. Access and build with SAIR today! 📰Read the Press Release: 📥Learn More and Download the Dataset at #DrugDiscovery #LQMs #SAIR #AIforScience #SandboxAQ
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Today we’re releasing SAIR, the Structurally Augmented IC50 Repository. SAIR is the Largest Open-Sourced Binding Affinity Dataset with Cofolded 3D Structures. It includes more than 5 million protein-ligand structures, generated using our Large Quantitative Models and labeled with binding affinity data. By providing this unprecedented scale of structure-activity data, we aim to enable researchers to train and evaluate new AI models for drug discovery, bridging the historical gap between molecular structures and drug potency prediction. The SAIR dataset was created using the NVIDIA DGX Cloud and is now publicly available on the Google Cloud Platform. Access and build with SAIR today! 📰Read the Press Release: 📥Learn More and Download the Dataset at #DrugDiscovery #LQMs #SAIR #AIforScience #SandboxAQ

SandboxAQ

129,416 görüntüleme • 1 yıl önce

We just released an open-source framework that makes it easy to build visual reasoning agents (with GRPO).
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We just released an open-source framework that makes it easy to build visual reasoning agents (with GRPO).

sunil kumar

108,525 görüntüleme • 1 yıl önce

🔥 West Ham United Fun Activation Setup⚽ 👇 Want training sessions plan? 📥 Download more training plans via:
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🔥 West Ham United Fun Activation Setup⚽ 👇 Want training sessions plan? 📥 Download more training plans via:

Keepitonthedeck

16,224 görüntüleme • 1 yıl önce

🚨New dataset + challenge #EMNLP2024🚨 We release ASL STEM Wiki: the first signing dataset of STEM articles! 📰 254 Wikipedia articles 📹 ~300 hours of ASL interpretations 👋 New task: automatic sign suggestion to make STEM education more accessible 🧵
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🚨New dataset + challenge #EMNLP2024🚨 We release ASL STEM Wiki: the first signing dataset of STEM articles! 📰 254 Wikipedia articles 📹 ~300 hours of ASL interpretations 👋 New task: automatic sign suggestion to make STEM education more accessible 🧵

Kayo Yin

15,279 görüntüleme • 1 yıl önce

📢📢𝐍𝐞𝐑𝐒𝐞𝐦𝐛𝐥𝐞 𝐯𝟐 𝐃𝐚𝐭𝐚𝐬𝐞𝐭 𝐑𝐞𝐥𝐞𝐚𝐬𝐞📢📢 Head captures of 7.1MP from 16 cameras at 73fps: * More recordings (425 people) * Better color calibration * Convenient download scripts The new version of our dataset adds 156 participants for a total of 425 different people. In its entirety, the dataset provides now 65 million images from over 15 hours of diverse human facial expression performances. We improved the color consistency of the recorded images with a better color calibration procedure. As a result, 3D reconstructions with images from the NeRSemble dataset should become better and look more realistic. Finally, we made it much easier to download the recordings with our new download repository. It now just takes a single command to download all frontal hair shake videos of all participants or to download all recordings of a single participant. Check it out: Awesome work by Tobias Kirschstein Simon Giebenhain !!!
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📢📢𝐍𝐞𝐑𝐒𝐞𝐦𝐛𝐥𝐞 𝐯𝟐 𝐃𝐚𝐭𝐚𝐬𝐞𝐭 𝐑𝐞𝐥𝐞𝐚𝐬𝐞📢📢 Head captures of 7.1MP from 16 cameras at 73fps: * More recordings (425 people) * Better color calibration * Convenient download scripts The new version of our dataset adds 156 participants for a total of 425 different people. In its entirety, the dataset provides now 65 million images from over 15 hours of diverse human facial expression performances. We improved the color consistency of the recorded images with a better color calibration procedure. As a result, 3D reconstructions with images from the NeRSemble dataset should become better and look more realistic. Finally, we made it much easier to download the recordings with our new download repository. It now just takes a single command to download all frontal hair shake videos of all participants or to download all recordings of a single participant. Check it out: Awesome work by Tobias Kirschstein Simon Giebenhain !!!

Matthias Niessner

12,089 görüntüleme • 1 yıl önce

🍌 Just released NanoBanana Pro LoRA Dataset Generator with fal Finally an easy way to create training datasets for: • Flux 2 • Z-Image • Qwen Image Edit • Any image-to-image model ✨ Uses Nano Banana Pro API on fal 🌐 100% browser-based - no server needed ⚡ Parallel generation for speed 🔗 Try it live: 💻 Code:
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🍌 Just released NanoBanana Pro LoRA Dataset Generator with fal Finally an easy way to create training datasets for: • Flux 2 • Z-Image • Qwen Image Edit • Any image-to-image model ✨ Uses Nano Banana Pro API on fal 🌐 100% browser-based - no server needed ⚡ Parallel generation for speed 🔗 Try it live: 💻 Code:

Lovis Odin

29,804 görüntüleme • 6 ay önce

✨ Adobe Firefly Video Model (beta) is released today!! ✨ It can do really well morphing objects. As Adobe has a lot of materials in its dataset I am impressed with results. if you want to rotate things just add “rotate around” to your prompt #CommunityXAdobe
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✨ Adobe Firefly Video Model (beta) is released today!! ✨ It can do really well morphing objects. As Adobe has a lot of materials in its dataset I am impressed with results. if you want to rotate things just add “rotate around” to your prompt #CommunityXAdobe

Kris Kashtanova

66,019 görüntüleme • 1 yıl önce

Post-training…
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Post-training…

Juanse Molina

20,754 görüntüleme • 10 ay önce

Today, we enter a new era of intelligence with Gemini 3. ✨ Our most intelligent model helps you bring any idea to life — offering state-of-the-art reasoning with unprecedented depth and nuance.
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Today, we enter a new era of intelligence with Gemini 3. ✨ Our most intelligent model helps you bring any idea to life — offering state-of-the-art reasoning with unprecedented depth and nuance.

Google UK

37,851,592 görüntüleme • 7 ay önce

because we can 🤗✨✋ experimenting with animation sequences in hand interfaces
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because we can 🤗✨✋ experimenting with animation sequences in hand interfaces

Kat ⊷ the Poet Engineer

107,517 görüntüleme • 1 yıl önce

Carolyne Marquez ~ post EMS training flexis Shop and more flexis :
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Carolyne Marquez ~ post EMS training flexis Shop and more flexis :

Carolyne Marquez

11,625 görüntüleme • 7 ay önce

New training method unlocked ✨
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New training method unlocked ✨

OtterOther

11,816 görüntüleme • 7 ay önce

NVIDIA + Stanford just dropped NitroGen "plays-any-game" AI trained on 40,000 hours of gameplay across 1,000+ games. They're releasing the dataset + model weights. 👇
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NVIDIA + Stanford just dropped NitroGen "plays-any-game" AI trained on 40,000 hours of gameplay across 1,000+ games. They're releasing the dataset + model weights. 👇

Min Choi

315,101 görüntüleme • 5 ay önce

Introduce CoT-VLA – Visual Chain-of-Thought reasoning for Robot Foundation Models! 🤖 By leveraging next-frame prediction as visual chain-of-thought reasoning, CoT-VLA uses future prediction to guide action generation and unlock large-scale video data for training. #CVPR2025
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Introduce CoT-VLA – Visual Chain-of-Thought reasoning for Robot Foundation Models! 🤖 By leveraging next-frame prediction as visual chain-of-thought reasoning, CoT-VLA uses future prediction to guide action generation and unlock large-scale video data for training. #CVPR2025

Qingqing Zhao

48,121 görüntüleme • 1 yıl önce

New open source LoRA Multi-Angles I created with fal for Flux.2 🔥 Flux2.-Lora-Multi-Angles: give a camera angle in degrees → get your image from that view. To build this, I created a system that captures 72 positions from Gaussian Splatting to generate the training dataset fully automatically in a webgl viewer. ▶️ Test: 📥 Weights: Should I open source my WebGL viewer so you can train your own from gaussian splatting ?
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New open source LoRA Multi-Angles I created with fal for Flux.2 🔥 Flux2.-Lora-Multi-Angles: give a camera angle in degrees → get your image from that view. To build this, I created a system that captures 72 positions from Gaussian Splatting to generate the training dataset fully automatically in a webgl viewer. ▶️ Test: 📥 Weights: Should I open source my WebGL viewer so you can train your own from gaussian splatting ?

Lovis Odin

43,693 görüntüleme • 6 ay önce

Spatial AI ( is building large real-world datasets to teach robots how to navigate the world and complete tasks. Their first open source dataset, SEA (Spatial Everyday Activities), is the largest curated egocentric dataset of people carrying out real tasks, with 10,000 hours of data.
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Spatial AI ( is building large real-world datasets to teach robots how to navigate the world and complete tasks. Their first open source dataset, SEA (Spatial Everyday Activities), is the largest curated egocentric dataset of people carrying out real tasks, with 10,000 hours of data.

Y Combinator

20,944 görüntüleme • 7 ay önce