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https://endpoints.huggingface.co/
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Hugging Face Inference Endpoints Images repository allows AI Builders to collaborate and engage creating awesome inference deployments

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mfuntowicz  updated a model 7 days ago
hfendpoints-images/embeddings-sentence-transformers-cpu
mfuntowicz  published a model 7 days ago
hfendpoints-images/embeddings-sentence-transformers-cpu
reach-vb  new activity 8 days ago
hfendpoints-images/README:Which models/ runners would you like to see next on Hugging face Endpoints
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hfendpoints-images's activity

AdinaY 
posted an update about 13 hours ago
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553
Matrix Game 🎮 an interactive foundation model for controllable game world generation, released by Skywork AI.

Skywork/Matrix-Game

✨ 17B with MIT licensed
✨ Diffusion-based image-to-world video generation via keyboard & mouse input
✨ GameWorld Score benchmark for Minecraft world models
✨ Massive Matrix Game Dataset with fine-grained action labels
AdinaY 
posted an update about 23 hours ago
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836
RoboBrain 🧠 an 32B open embodied AI model enabling multi-robot collaboration, released by BAAIBeijing.

Model: BAAI/robobrain-681e1389c64d06b3e4a45e44
Dataset: BAAI/ShareRobot

✨ Task decomposition into 20+ precise actions
✨ Operable region detection (e.g: teapot handles, drawers)
✨ Motion trajectory prediction to avoid collisions
AdinaY 
posted an update about 24 hours ago
AdinaY 
posted an update 4 days ago
clem 
posted an update 5 days ago
clem 
posted an update 7 days ago
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3945
What are you using to evaluate models or AI systems? So far we're building lighteval & leaderboards on the hub but still feels early & a lot more to build. What would be useful to you?
·
AdinaY 
posted an update 7 days ago
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3851
ACE-Step 🎵 a music generation foundation model released by
StepFun & ACEStudio

Model: ACE-Step/ACE-Step-v1-3.5B
Demo: ACE-Step/ACE-Step

✨ 3.5B, Apache2.0 licensed
✨ 115× faster than LLMs (4-min music in 20s on A100)
✨ Diffusion + DCAE + linear transformer = speed + coherence
✨ Supports voice cloning, remixing, lyric editing & more
  • 1 reply
·
AdinaY 
posted an update 7 days ago
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801
CCI4.0-M2 📊 A powerful dataset with 3 specialized subsets, released by
BAAIBeijing

BAAI/cci40-68199d90bbc798680df16d7c

✨ M2-Base: 3.5TB web data (EN/ZH), with LLM-augmented content, APACHE2.0
✨ M2-CoT: 4.2TB of auto-synthesized CoT reasoning data
✨ M2-Extra: domain-specific knowledge
mfuntowicz 
updated a model 7 days ago
mfuntowicz 
published a model 7 days ago
linoyts 
posted an update 8 days ago
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2462
FramePack is hands down one of the best OS releases in video generation 🙇🏻‍♀️🤯
✅ fully open sourced + amazing quality + reduced memory + improved speed
but more even - its gonna facilitate *soooo* many downstream applications
like this version adapted for landscape rotation 👇https://huggingface.co/spaces/tori29umai/FramePack_rotate_landscape
  • 2 replies
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reach-vb 
in hfendpoints-images/README 8 days ago

Which models/ runners would you like to see next on Hugging face Endpoints
#2 opened 8 days ago by
reach-vb

Update README.md
#1 opened 8 days ago by
reach-vb
reach-vb 
published a Space 8 days ago
mfuntowicz 
updated a model 10 days ago
mfuntowicz 
in hfendpoints-images/text-generation-sglang-gpu 11 days ago

feat(quant): allow using native precision
#3 opened 11 days ago by
mfuntowicz
clem 
posted an update 11 days ago
evijit 
authored a paper 11 days ago
clem 
posted an update 11 days ago
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1497
The meta-llama org just crossed 40,000 followers on Hugging Face. Grateful for all their impact on the field sharing the Llama weights openly and much more!

We need more of this from all other big tech to make the AI more open, collaborative and beneficial to all!
abidlabs 
posted an update 12 days ago
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3884
HOW TO ADD MCP SUPPORT TO ANY 🤗 SPACE

Gradio now supports MCP! If you want to convert an existing Space, like this one hexgrad/Kokoro-TTS, so that you can use it with Claude Desktop / Cursor / Cline / TinyAgents / or any LLM that supports MCP, here's all you need to do:

1. Duplicate the Space (in the Settings Tab)
2. Upgrade the Gradio sdk_version to 5.28 (in the README.md)
3. Set mcp_server=True in launch()
4. (Optionally) add docstrings to the function so that the LLM knows how to use it, like this:

def generate(text, speed=1):
    """
    Convert text to speech audio.

    Parameters:
        text (str): The input text to be converted to speech.
        speed (float, optional): Playback speed of the generated speech.


That's it! Now your LLM will be able to talk to you 🤯