ASSERT-KTH / ASSERT-KTH/VRepair
Pre-trained of best models
- Dominant language
- C
- Stars
- 63
- Forks
- 17
- PR merge metrics
- No merged PRs in 30d
Description
Hi @chenzimin ,
The models that you provided (~270GB) is currently too large for me to handle right now and using my current resource to re-train the best model according to your report is not possible for me right now either(I had to reduce the attention heads to 3 for the model to train without the out-of-memory error). From what I understand, the models that you provided in the onedrive is all the models that you trained during the ablation study so is it possible for you to upload only your best models (preferably somewhere I can `wget` my linux server cause using onedrive force me to first download it to my local then reupload to the server) ?
Thank you a lot.
Best regards,
Dang
Contributor guide
No contributing guide indexed for this repository
Research direction
No source file, test, or entry point is mentioned. First clarify which models from the ablation study are considered the best and where they should be hosted for wget access. Done means the selected pretrained models are available for download without requiring the full ~270GB collection.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- c, machine-learning
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 15/100