Post
10522
THIS IS CRAZY! THE MODEL ON THE IMAGE(Supra-50M-Reasoning) answered correctly and its QUANTIZED IN 2BIT! THE RESPONSE IS CORRECT, IN A 15MB SIZE FILE!
- 13 replies
Lucas Silva PRO
YuLexuan30
AI & ML interests
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upvoted a changelog 3 days ago
Filter Models page by Base Models only new activity 3 days ago
Comfy-Org/Ideogram-4:Nvfp4 vs nf4Organizations
reacted to AxionLab-official's post with 👀 2 days ago
upvoted a changelog 3 days ago
Hugging Face Changelog
Filter Models page by Base Models only
• 144
Nvfp4 vs nf4
4
#3 opened 4 days ago
by 
realrebelai
reacted to danielhanchen's post with 🔥 3 days ago
Post
8720
Gemma 4 12B can now run locally on just 8GB RAM via Dynamic GGUFs.
Google's new model, Gemma 4 12B Unified supports image, audio and 256K context.
You can run and train the model via Unsloth Studio.
GGUF: unsloth/gemma-4-12b-it-GGUF
Guide: https://unsloth.ai/docs/models/gemma-4
Google's new model, Gemma 4 12B Unified supports image, audio and 256K context.
You can run and train the model via Unsloth Studio.
GGUF: unsloth/gemma-4-12b-it-GGUF
Guide: https://unsloth.ai/docs/models/gemma-4
- 4 replies
Asking Public to give so much hatred for this space, spamming as much as possible because I think This is done on purpose
2
#51 opened 16 days ago
by 
Matejstein
Can someone please create New Nano banana pro Space for hugging face?
😔 2
1
#55 opened 14 days ago
by Matejstein
upvoted a changelog 19 days ago
Hugging Face Changelog
Filter Leaderboards by Model Size
• 121
reacted to PhysiQuanty's post with 🔥 25 days ago
Post
5143
❗ Dating apps do not allow us to control the profiles suggested to us based on our mutual search criteria ❗
🧬 If you want to see if your soulmate has already existed, I have published a dataset of 59k anonymized public profiles
SpiceeChat/OkCupid-59k-Anonymized-Profiles
Are you looking for a female ML engineer who is looking for a male ML engineer and you can't find it on the apps ?
You need to look for her, but more importantly, she needs to look for you.
Personally, I'm looking for a physicist I'm encountering the same problem. I can't find it
My answer : Paradox of choice of dating apps solved by patent ⚡ WO2026082672 ⚡
https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2026082672
J'ai du breveté pour te trouver et on se trouvera bientôt !
🧬 If you want to see if your soulmate has already existed, I have published a dataset of 59k anonymized public profiles
SpiceeChat/OkCupid-59k-Anonymized-Profiles
Are you looking for a female ML engineer who is looking for a male ML engineer and you can't find it on the apps ?
You need to look for her, but more importantly, she needs to look for you.
Personally, I'm looking for a physicist I'm encountering the same problem. I can't find it
My answer : Paradox of choice of dating apps solved by patent ⚡ WO2026082672 ⚡
https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2026082672
J'ai du breveté pour te trouver et on se trouvera bientôt !
- 9 replies
Developer mode enabled, please disable
3
#43 opened 25 days ago
by YuLexuan30
reacted to blanchon's post with 🚀 25 days ago
Post
2639
I'm releasing OpenCS2 a 11TB dataset of around 5000 hours of counter strike gameplay recording.
- HD resolution - 1280×720 · 32 fps
- For each frame keyboard and mouse + world state (player position, velocity, weapon ...)
- HD Stereo audio
- All 10 players perspective
https://huggingface.co/collections/blanchon/opencs2
- HD resolution - 1280×720 · 32 fps
- For each frame keyboard and mouse + world state (player position, velocity, weapon ...)
- HD Stereo audio
- All 10 players perspective
https://huggingface.co/collections/blanchon/opencs2
- 1 reply
reacted to Imosu's post with 👀 25 days ago
Post
3334
# ZeroGPU Hardware Mismatch: Why Am I Getting RTX PRO 6000 Blackwell MIG Instead of the Documented H200?
I recently ran into a surprising issue while debugging a Hugging Face ZeroGPU Space.
According to the Hugging Face ZeroGPU documentation, ZeroGPU is described as using NVIDIA H200-based resources, with configurations such as “large” and “xlarge” offering H200-class memory. However, when I printed the actual GPU information inside my Space, I got something different:
GPU: NVIDIA RTX PRO 6000 Blackwell Server Edition MIG 2g.48gb
Capability: (12, 0)
Torch: 2.8.0+cu128
CUDA: 12.8
This is not an H200. It appears to be a MIG slice of an RTX PRO 6000 Blackwell Server Edition GPU, with 48GB VRAM.
This difference matters. It is not just a cosmetic hardware-name issue.
In my case, the Space was running Qwen3-TTS and failed with:
CUDA error:
no kernel image is available for execution on the device
The issue appears related to GPU architecture compatibility. The app was using kernels-community/flash-attn3, which is generally aligned with Hopper-class GPUs such as H100/H200, but the actual device exposed to the Space was Blackwell with compute capability 12.0. As a result, CUDA kernels that might work on the expected H200 environment failed on the actual assigned GPU.
To be clear, I am not saying the RTX PRO 6000 Blackwell is a bad GPU. It is a newer architecture and may be powerful in many workloads. But it is not the same as H200, and the software ecosystem compatibility is different. For ML workloads, especially those relying on custom CUDA kernels, the exact GPU architecture matters a lot.
This raises a few questions:
Is Hugging Face ZeroGPU now assigning RTX PRO 6000 Blackwell MIG instances instead of H200 instances?
If yes, why is this not clearly documented?
I recently ran into a surprising issue while debugging a Hugging Face ZeroGPU Space.
According to the Hugging Face ZeroGPU documentation, ZeroGPU is described as using NVIDIA H200-based resources, with configurations such as “large” and “xlarge” offering H200-class memory. However, when I printed the actual GPU information inside my Space, I got something different:
GPU: NVIDIA RTX PRO 6000 Blackwell Server Edition MIG 2g.48gb
Capability: (12, 0)
Torch: 2.8.0+cu128
CUDA: 12.8
This is not an H200. It appears to be a MIG slice of an RTX PRO 6000 Blackwell Server Edition GPU, with 48GB VRAM.
This difference matters. It is not just a cosmetic hardware-name issue.
In my case, the Space was running Qwen3-TTS and failed with:
CUDA error:
no kernel image is available for execution on the device
The issue appears related to GPU architecture compatibility. The app was using kernels-community/flash-attn3, which is generally aligned with Hopper-class GPUs such as H100/H200, but the actual device exposed to the Space was Blackwell with compute capability 12.0. As a result, CUDA kernels that might work on the expected H200 environment failed on the actual assigned GPU.
To be clear, I am not saying the RTX PRO 6000 Blackwell is a bad GPU. It is a newer architecture and may be powerful in many workloads. But it is not the same as H200, and the software ecosystem compatibility is different. For ML workloads, especially those relying on custom CUDA kernels, the exact GPU architecture matters a lot.
This raises a few questions:
Is Hugging Face ZeroGPU now assigning RTX PRO 6000 Blackwell MIG instances instead of H200 instances?
If yes, why is this not clearly documented?
- 2 replies
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