I made a full tutorial for TRELLIS - all pre-compiled libraries - 1-Click to Install - Fully supporting RTX 5000 series and older GPUs with Python VENV
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 13.7k
- Forks
- 1.3k
- PR merge metrics
- No merged PRs in 30d
Description
Thank you so much Microsoft Team. If you are not ok with this post you can close it.
Edit : my installer uses a backup repo now so it works
Installing TRELLIS for RTX 5000 series on Windows is a nightmare. But I made it effortlessly work after working few days. Also the advanced Gradio App has so many features including as low as 6 GB VRAM with offloading and FP16 (I thank trellis-stable-projectorz a lot)
Moreover I have RunPod and Massed Compute installers so GPU poor can also run this app very easily. I compiled Libraries for Linux as well.
Tutorial link : https://youtu.be/EhU7Jil9WAk
Step by Step TRELLIS Tutorial to Generate Amazing High-Quality 3D Assets from Static Images Locally
Our App interface below
Few examples
https://github.com/user-attachments/assets/3a6b288b-dd1d-4405-857f-aeb28eef9775
https://github.com/user-attachments/assets/04ba7333-4c48-40f3-a70e-6a2701092d22
https://github.com/user-attachments/assets/f3439024-0131-466e-86bf-2d084950915f
https://github.com/user-attachments/assets/0bd271b3-317a-4cf8-8c10-26aac8172771
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue provides a YouTube tutorial and describes Windows, Linux, RunPod, Massed Compute, Gradio, and GPU installation support, but names no repository file, test, or entry point. Start by reviewing the linked tutorial against the repository's existing installation guidance; a useful contribution would need a maintainer-approved documentation location and a clearly defined scope.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100
