Post
1989
Since when are H200s on ZeroGPU?
- 2 replies
Join the conversation
Join the community of Machine Learners and AI enthusiasts.
Sign UpAll HF Hub posts
nroggendorff
posted an update
1 day ago
Post
2155
LiquidAI
open-sources a new generation of edge LLMs! 🥳Based on a new hybrid architecture, these 350M, 700M, and 1.2B models are both fast and performant, ideal for on-device deployment.
I recommend fine-tuning them to power your next edge application. We already provide Colab notebooks to guide you. More to come soon!
📝 Blog post: https://www.liquid.ai/blog/liquid-foundation-models-v2-our-second-series-of-generative-ai-models
🤗 Models: LiquidAI/lfm2-686d721927015b2ad73eaa38
Post
1587
I am happy to announce that Ark now supports the following robots:
1. Franka Panda
2. Kuka LWR
3. UFactory XArm
4. Husky Robot
Everything is done in Python. You can even control your robot from a Jupiter notebook.
Check out the tutorials: https://arkrobotics.notion.site/ARK-Home-22be053d9c6f8096bcdbefd6276aba61
Check out the code: https://github.com/orgs/Robotics-Ark/repositories
Check out the documentation: https://robotics-ark.github.io/ark_robotics.github.io/docs/html/index.html
Check out the paper: https://robotics-ark.github.io/ark_robotics.github.io/static/images/ark_framework_2025.pdf
Hope you find it useful. Let us know if you want a specific feature! We would love to support you 😄
1. Franka Panda
2. Kuka LWR
3. UFactory XArm
4. Husky Robot
Everything is done in Python. You can even control your robot from a Jupiter notebook.
Check out the tutorials: https://arkrobotics.notion.site/ARK-Home-22be053d9c6f8096bcdbefd6276aba61
Check out the code: https://github.com/orgs/Robotics-Ark/repositories
Check out the documentation: https://robotics-ark.github.io/ark_robotics.github.io/docs/html/index.html
Check out the paper: https://robotics-ark.github.io/ark_robotics.github.io/static/images/ark_framework_2025.pdf
Hope you find it useful. Let us know if you want a specific feature! We would love to support you 😄
- 4 replies
sergiopaniego
posted an update
2 days ago
Post
1314
Test SmolLM3, the newest fully open model released by
@HuggingFaceTB
!
It's smol (3B), multilingual (6 languages), comes with dual mode reasoning (think/no_think modes) and supports long-context (128k).
Try it now in the notebook below!! ⬇️
Colab notebook: https://colab.research.google.com/github/sergiopaniego/samples/blob/main/smollm3_3b_inference.ipynb
notebook: https://github.com/sergiopaniego/samples/blob/main/smollm3_3b_inference.ipynb
blog: https://huggingface.co/blog/smollm3
It's smol (3B), multilingual (6 languages), comes with dual mode reasoning (think/no_think modes) and supports long-context (128k).
Try it now in the notebook below!! ⬇️
Colab notebook: https://colab.research.google.com/github/sergiopaniego/samples/blob/main/smollm3_3b_inference.ipynb
notebook: https://github.com/sergiopaniego/samples/blob/main/smollm3_3b_inference.ipynb
blog: https://huggingface.co/blog/smollm3
MonsterMMORPG
posted an update
1 day ago
Post
1206
MultiTalk (from MeiGen) Full Tutorial With 1-Click Installer - Make Talking and Singing Videos From Static Images - Moreover shows how to setup and use on RunPod and Massed Compute private cheap cloud services as well
Tutorial video link > https://youtu.be/8cMIwS9qo4M
Video Chapters
0:00 Intro & MultiTalk Showcase
0:28 Singing Animation Showcase
0:57 Tutorial Structure Overview (Windows, Massed Compute, RunPod)
1:10 Windows - Step 1: Download & Extract the Main ZIP File
1:43 Windows - Prerequisites (Python, Git, CUDA, FFmpeg)
2:12 Windows - How to Perform a Fresh Installation (Deleting venv & custom_nodes)
2:42 Windows - Step 2: Running the Main ComfyUI Installer Script
4:24 Windows - Step 3: Installing MultiTalk Nodes & Dependencies
5:05 Windows - Step 4: Downloading Models with the Unified Downloader
6:18 Windows - Tip: Setting Custom Model Paths in ComfyUI
7:18 Windows - Step 5: Updating ComfyUI to the Latest Version
7:39 Windows - Step 6: Launching ComfyUI
7:53 Workflow Usage - Using the 480p 10-Second Workflow
8:07 Workflow Usage - Configuring Basic Parameters (Image, Audio, Resolution)
8:55 Workflow Usage - Optimizing Performance: 'Blocks to Swap' & GPU Monitoring
9:49 Workflow Usage - Crucial Step: Calculating & Setting the Number of Frames
10:48 Workflow Usage - First Generation: Running the 480p Workflow
12:01 Workflow Usage - Troubleshooting: How to Fix 'Out of VRAM' Errors
13:51 Workflow Usage - Introducing the High-Quality Long Context Workflow (720p)
14:09 Workflow Usage - Configuring the 720p 10-Step High-Quality Workflow
16:18 Workflow Usage - Selecting the Correct Model (GGUF) & Attention Mechanism
17:58 Workflow Usage - Improving Results by Changing the Seed
18:36 Workflow Usage - Side-by-Side Comparison: 480p vs 720p High-Quality
20:26 Workflow Usage - Behind the Scenes: How the Intro Videos Were Made
21:32 Part 2: Massed Compute Cloud GPU Tutorial
22:03 Massed Compute - Deploying a GPU Instance (H100)
.
.
.
Tutorial video link > https://youtu.be/8cMIwS9qo4M
Video Chapters
0:00 Intro & MultiTalk Showcase
0:28 Singing Animation Showcase
0:57 Tutorial Structure Overview (Windows, Massed Compute, RunPod)
1:10 Windows - Step 1: Download & Extract the Main ZIP File
1:43 Windows - Prerequisites (Python, Git, CUDA, FFmpeg)
2:12 Windows - How to Perform a Fresh Installation (Deleting venv & custom_nodes)
2:42 Windows - Step 2: Running the Main ComfyUI Installer Script
4:24 Windows - Step 3: Installing MultiTalk Nodes & Dependencies
5:05 Windows - Step 4: Downloading Models with the Unified Downloader
6:18 Windows - Tip: Setting Custom Model Paths in ComfyUI
7:18 Windows - Step 5: Updating ComfyUI to the Latest Version
7:39 Windows - Step 6: Launching ComfyUI
7:53 Workflow Usage - Using the 480p 10-Second Workflow
8:07 Workflow Usage - Configuring Basic Parameters (Image, Audio, Resolution)
8:55 Workflow Usage - Optimizing Performance: 'Blocks to Swap' & GPU Monitoring
9:49 Workflow Usage - Crucial Step: Calculating & Setting the Number of Frames
10:48 Workflow Usage - First Generation: Running the 480p Workflow
12:01 Workflow Usage - Troubleshooting: How to Fix 'Out of VRAM' Errors
13:51 Workflow Usage - Introducing the High-Quality Long Context Workflow (720p)
14:09 Workflow Usage - Configuring the 720p 10-Step High-Quality Workflow
16:18 Workflow Usage - Selecting the Correct Model (GGUF) & Attention Mechanism
17:58 Workflow Usage - Improving Results by Changing the Seed
18:36 Workflow Usage - Side-by-Side Comparison: 480p vs 720p High-Quality
20:26 Workflow Usage - Behind the Scenes: How the Intro Videos Were Made
21:32 Part 2: Massed Compute Cloud GPU Tutorial
22:03 Massed Compute - Deploying a GPU Instance (H100)
.
.
.
jbilcke-hf
posted an update
2 days ago
Post
2320
Are you looking to run a robot simulator, maybe run long robot policy training tasks, but you don't have the GPU at home?
Well.. you can run MuJoCo inside a Hugging Face space!
All you have to do is to clone this space:
jbilcke-hf/train-robots-with-mujoco
Don't forget to a pick a Nvidia GPU for your space, to be able to get some nice OpenGL renders!
Are you new to MuJoCo and/or JupyterLab notebooks?
You can get started with this tutorial (select "Open from URL" then paste the URL to this notebook):
jbilcke-hf/train-robots-with-mujoco
Happy robot hacking! 🦾
Well.. you can run MuJoCo inside a Hugging Face space!
All you have to do is to clone this space:
jbilcke-hf/train-robots-with-mujoco
Don't forget to a pick a Nvidia GPU for your space, to be able to get some nice OpenGL renders!
Are you new to MuJoCo and/or JupyterLab notebooks?
You can get started with this tutorial (select "Open from URL" then paste the URL to this notebook):
jbilcke-hf/train-robots-with-mujoco
Happy robot hacking! 🦾
- 2 replies
Post
2647
How to achieve 100% Pass Rate on HumanEval ? 🔥
Meet MGDebugger if you are tired of LLMs failing on complex bugs 🤔 Our MGDebugger, just hit 100% accuracy on HumanEval using the DeepSeek-R1 model. 🚀
✨ Demo: learnmlf/MGDebugger
📝 Paper: From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging (2410.01215)
💻 Code: https://github.com/YerbaPage/MGDebugger
HumanEval may be retired, we're ready for the next challenge In more complex scenarios! You may also take look at this repo for a collection of awesome repo-level coding tasks!
🖥️ https://github.com/YerbaPage/Awesome-Repo-Level-Code-Generation
Meet MGDebugger if you are tired of LLMs failing on complex bugs 🤔 Our MGDebugger, just hit 100% accuracy on HumanEval using the DeepSeek-R1 model. 🚀
✨ Demo: learnmlf/MGDebugger
📝 Paper: From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging (2410.01215)
💻 Code: https://github.com/YerbaPage/MGDebugger
HumanEval may be retired, we're ready for the next challenge In more complex scenarios! You may also take look at this repo for a collection of awesome repo-level coding tasks!
🖥️ https://github.com/YerbaPage/Awesome-Repo-Level-Code-Generation
Post
91
🚀 Announcing the Synthetic-to-Real Multi-Class Object Detection Challenge!
We’re excited to announce the launch of the Synthetic-to-Real Multi-Class Object Detection Challenge—now live on Kaggle!
This exciting competition is brought to you by 3LC in partnership with Duality AI, creators of the powerful FalconCloud tool for generating targeted synthetic data. Together, we're offering a unique opportunity to push the boundaries of object detection through high-fidelity, simulation-to-real workflows.
🧪 What Makes This Challenge Special?
💻 Create customized training data with Duality’s cloud-based scenario
🧠 Analyze data weaknesses and take precise, data-driven actions using 3LC's robust tooling
⚙️ Optimize data for peak model training
🏆 Why Join?
• Win cash prizes, certificates, and global recognition
• Gain exposure to real-world simulation workflows used in top AI companies
• Collaborate and compete with leading minds in computer vision, ML, and AI
Whether you're a student, researcher, or industry pro, this challenge is your chance to bridge the Sim2Real gap and showcase your skills in building high-performance object detection models.
🔗 Ready to compete?
https://www.kaggle.com/competitions/multi-class-object-detection-challenge
We’re excited to announce the launch of the Synthetic-to-Real Multi-Class Object Detection Challenge—now live on Kaggle!
This exciting competition is brought to you by 3LC in partnership with Duality AI, creators of the powerful FalconCloud tool for generating targeted synthetic data. Together, we're offering a unique opportunity to push the boundaries of object detection through high-fidelity, simulation-to-real workflows.
🧪 What Makes This Challenge Special?
💻 Create customized training data with Duality’s cloud-based scenario
🧠 Analyze data weaknesses and take precise, data-driven actions using 3LC's robust tooling
⚙️ Optimize data for peak model training
🏆 Why Join?
• Win cash prizes, certificates, and global recognition
• Gain exposure to real-world simulation workflows used in top AI companies
• Collaborate and compete with leading minds in computer vision, ML, and AI
Whether you're a student, researcher, or industry pro, this challenge is your chance to bridge the Sim2Real gap and showcase your skills in building high-performance object detection models.
🔗 Ready to compete?
https://www.kaggle.com/competitions/multi-class-object-detection-challenge
Post
186
Kimi-K2 is now available on the hub🔥🚀
This is a trillion-parameter MoE model focused on long context, code, reasoning, and agentic behavior.
moonshotai/kimi-k2-6871243b990f2af5ba60617d
✨ Base & Instruct
✨ 1T total / 32B active - Modified MIT License
✨ 128K context length
✨ Muon optimizer for stable trillion-scale training
This is a trillion-parameter MoE model focused on long context, code, reasoning, and agentic behavior.
moonshotai/kimi-k2-6871243b990f2af5ba60617d
✨ Base & Instruct
✨ 1T total / 32B active - Modified MIT License
✨ 128K context length
✨ Muon optimizer for stable trillion-scale training
- 1 reply
dylanebert
posted an update
2 days ago
Post
2091
dylanebert/3d-arena now supports topology-only voting and ranking!
Let's see which Gen3D model produces the best topology
Let's see which Gen3D model produces the best topology
