RosettaCommons / RosettaCommons/RFdiffusion

Inquiry Regarding Running RFdiffusion Colab Notebook (diffusion.ipynb) on ARM64 Architecture (Jupyter Notebook Attempt Failed)

Open
#374 6 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
3.1k
Forks
644
PR merge metrics
No merged PRs in 30d

Description

Dear RFdiffusion / DGL Team,

I am writing to you with great interest in the RFdiffusion project. I've been attempting to run the code from your Colab Notebook (https://colab.research.google.com/github/sokrypton/ColabDesign/blob/v1.1.1/rf/examples/diffusion.ipynb#scrollTo=pZQnHLuDCsZm) on an ARM64 architecture environment.

Unfortunately, I have encountered difficulties and failed to execute the code using a Jupyter Notebook on my ARM64-based system. I was hoping you could provide some guidance. Is there a recommended way to get this code running on an ARM64 environment? I would be most grateful if you could share any specific installation instructions, dependency configurations, or recommended execution procedures for ARM64.

Furthermore, any insights into potential challenges or considerations I should be aware of when targeting this architecture would be immensely helpful.

Thank you for your time and assistance.

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the linked diffusion.ipynb Colab notebook and review its installation and execution steps against the reported ARM64 environment. Reproduce the failure if possible, then determine whether a supported ARM64 procedure can be documented or whether the architecture is unsupported.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook, python
Domain
machine-learning
Issue type
Bug
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.