RosettaCommons / RosettaCommons/RFdiffusion
Instructions for fine-tuning
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- Dominant language
- Python
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Description
Hi,
First of all – thanks much for all your work, what an amazing tool you've built here!
I am very curious to know if you had any form of formalized documentation on how one could fine-tune the model on a specific dataset? Interested mostly if there is anything to note when running training. I would also be interested in compute requirements, potential existing evaluation scripts, and so on.
Thanks in advance! Best,
Arnaud
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
Start by reviewing the repository's existing training and evaluation material, since the issue does not name specific files or entry points. Document how to fine-tune on a specific dataset, training considerations, compute requirements, and available evaluation scripts. Done means the requested guidance is organized and complete enough for a user to follow.
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
- Mostly clear
- Newbie friendliness
- 32/100