Hi @qiisun 🤗
I'm Niels, part of the community science team at Hugging Face.
First, congratulations on MeshFlow getting accepted to SIGGRAPH 2026! It looks like a really impressive and fast approach to direct 3D mesh generation.
I noticed that you have already uploaded your dataset and model checkpoints to Hugging Face under the dataset repository: https://huggingface.co/datasets/qsun2001/meshflow. This is awesome!
However, since you have released 4 pre-trained checkpoints (for bench, chair, lamp, and table categories), would you like to host them on the Hugging Face Model Hub (https://huggingface.co/models) instead of keeping the .pt files inside the dataset repository?
Hosting your checkpoints as proper model repositories on Hugging Face provides several key benefits:
- Better Discoverability: They will be categorized and searchable as machine learning models, making them much easier for the 3D generation community to find.
- Individual Download Statistics: You will get dedicated download tracking and analytics for each of your model checkpoints.
- Structured Metadata & Model Cards: You can add specific model cards, metadata tags (like PyTorch, 3D, or custom categories), and cleanly separate your training data from your model checkpoints.
- Paper Page Integration: Once uploaded to the Model Hub, we can link each model directly to your official Hugging Face Paper Page (https://huggingface.co/papers/2606.23489), so readers can find your models instantly.
Additionally, since you already have a gradio_demo.py script in your repository, you can easily build an interactive web demo for MeshFlow on Spaces. We can provide you with a free ZeroGPU grant, which gives you free GPU-backed compute for eligible demo Spaces.
If you are open to it, you can easily create model repositories via the UI or CLI and upload your weights. Here is a quick guide on uploading models to the Hub.
Let me know if you are interested or if you need any assistance with this!
Best regards,
Niels
ML Engineer @ HF 🤗
Hi @qiisun 🤗
I'm Niels, part of the community science team at Hugging Face.
First, congratulations on MeshFlow getting accepted to SIGGRAPH 2026! It looks like a really impressive and fast approach to direct 3D mesh generation.
I noticed that you have already uploaded your dataset and model checkpoints to Hugging Face under the dataset repository: https://huggingface.co/datasets/qsun2001/meshflow. This is awesome!
However, since you have released 4 pre-trained checkpoints (for bench, chair, lamp, and table categories), would you like to host them on the Hugging Face Model Hub (https://huggingface.co/models) instead of keeping the
.ptfiles inside the dataset repository?Hosting your checkpoints as proper model repositories on Hugging Face provides several key benefits:
Additionally, since you already have a
gradio_demo.pyscript in your repository, you can easily build an interactive web demo for MeshFlow on Spaces. We can provide you with a free ZeroGPU grant, which gives you free GPU-backed compute for eligible demo Spaces.If you are open to it, you can easily create model repositories via the UI or CLI and upload your weights. Here is a quick guide on uploading models to the Hub.
Let me know if you are interested or if you need any assistance with this!
Best regards,
Niels
ML Engineer @ HF 🤗