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is there a better guide for BLIP or CLIP pretraining? #4

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simplelifetime opened this issue Sep 22, 2022 · 4 comments
Closed

is there a better guide for BLIP or CLIP pretraining? #4

simplelifetime opened this issue Sep 22, 2022 · 4 comments
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documentation Improvements or additions to documentation

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@simplelifetime
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Thank you for your great work! I was wondering how should implement image-text pre-training for CLIP or BLIP, which seems unclear in the project readme files.

@dxli94
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dxli94 commented Sep 22, 2022

Thanks for your interest in LAVIS.

  • please refer to run_scripts/blip/train/pretrain.sh as the entry point for pretraining BLIP. The configuration file is lavis/projects/blip/train/pretrain_14m.yaml.
  • before pretraining, you may want to prepare datasets. Please refer to https://github.com/salesforce/LAVIS/tree/main/lavis/datasets/download_scripts for downloading datasets.
  • to better understand how training in LAVIS works, please refer to https://opensource.salesforce.com/LAVIS//latest/tutorial.training-example.html for an example.
  • Your feedback is well received. We've noted it down and try to come up with more documentations on this.
  • We have not tested CLIP pre-training.

Thanks!

@dxli94 dxli94 added the documentation Improvements or additions to documentation label Sep 22, 2022
@simplelifetime
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Thank you for your reply. And i notice that the notebook files broken in https://github.com/salesforce/LAVIS/tree/main/lavis/datasets/download_scripts/DownloadConceptualCaptions I'm not sure if it's my problem or it's actually broken

@dxli94
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dxli94 commented Sep 22, 2022

Hi @simplelifetime, thanks a lot for well-spotting. I've removed incorrect license headers in the notebook. Can you pull and see whether it works as expected?

Thanks.

@simplelifetime
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It works fine now, thanks for your support!

anthonytmh pushed a commit to anthonytmh/lavis-pnpvqa that referenced this issue Mar 24, 2023
Instruction Tuning - Multitask Evaluation [Done]
dxli94 added a commit that referenced this issue Jul 10, 2023
* change sample keywards for inference; add example notebooks.

* update README.

* upload checkpoint to gcloud.

* remove unused print.

* add embed youtube video.

* remove embedded video.

* remove ununsed script.

* final touch

* remove unused notebooks.

* remove unused script.

* remove unused scripts.

* rerun notebook.

* re-merge the notebooks.
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