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Hi @bbrattoli, have you done any work or experiments on transferring the weights of the self-supervised model to a new model for transfer learning/semi-supervised learning for classification or detect…
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## 🚀 Feature
Support ADE20k for semantic segmentation with deeplabv3+
## Motivation & Examples
This will be helpful when people need to benchmark different self-supervised learning method, sinc…
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You had mentioned that the backbone network is ResNet-50 pretrained on Imagenet.
https://github.com/thuml/Universal-Domain-Adaptation/blob/5d7caa95af7e3675305c542253c4e372801897d2/net.py#L37
Bu…
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- ML test-bench style
- streaming data? or fixed corpus? (transfer costs excessive on Azure - probably want a fixed corpus)
- two corpuses: [DL S2 DLSR, S1] and [L2A, EES1]
- pytorch
- pytorch par…
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Congratulations for your excellent work!
I want to commit semi-supervised experiments on Pascal Context dataset and compare the results with your work. So could you plz offer me the data-split files …
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Hi DropEdge Team,
I am running experiments on 8-layer GCN (using DropEdge) in the semi-supervised setting. I used the default hyper-parameters as 2-layer GCN and changed `--nbaseblocklayer 0` to `-…
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*Note:* I should also try some experiments with supervised ImageNet pretrained models. A lot of the stuff here will be the same as for them, but I'll just focus on SimCLR stuff here.
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I was running `mteb run -m McGill-NLP/LLM2Vec-Llama-2-7b-chat-hf-mntp-supervised -t DBPedia ArguAna NFCorpus FiQA2018 --output_folder results_0 --device 0 `
But I got:
File "/mnt/ceph_home/…
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Hi! Thank you for the codebase. Could you please list the commands necessary to reproduce the experiments from your paper with CUB? I would like to cite the paper but I'd like to verify the results f…
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I enjoyed reading the paper and very promising results. Are you planning to share the code of ImageNet experiments in semi-supervised setting ? It would be a great help to reproduce the results.