dimensionalOS / dimensionalOS/dimos
Installer: more Jetson wheels
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 4.5k
- Forks
- 808
- Avg merge
- 3d 5h
- Merged PRs (30d)
- 233
Description
- jetson setup could use more pytorch wheels (we are already at 5 library forks, whats one more 🙄)
- use this as a template: https://github.com/jeff-hykin/onnxruntime-gpu-extended
update instructions so that codex doesn't say this next time for a jetson;
One limitation remains: GPU-enabled PyTorch. The installer chose PyTorch 2.13.0+cu130, but JetPack 6.2.1 provides a CUDA 12.6 driver. I fixed the generated Nix configuration so Jetson driver libraries are visible, but CUDA 13 PyTorch still cannot run against the 12.6 driver. NVIDIA lists JetPack 6.2 PyTorch support through compatible framework containers rather than a standalone wheel.
Synced from DIM-1496 by jeff
Contributor guide
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
Start by locating the existing Jetson setup and installer instructions, then compare their PyTorch wheel handling with the linked onnxruntime-gpu-extended template. Verify the available JetPack-compatible wheels and update the instructions so Jetson setup no longer reports the stated GPU-enabled PyTorch limitation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- build-system, embedded-iot, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100