Comments (1)
sunanhe
commented on July 19, 2024
The label embeddings in the first training stage are generated by the bert of pretrained CLIP model.
Best,
Sunan
from mkt.
Related Issues (20)
- negative samples in ranking loss? HOT 1
- nus_wide_test.h5，nus_wide_train.h5 unavailable HOT 2
- TP = (labels[mask] == 1).sum().float() RuntimeError: CUDA error: device-side assert triggered HOT 1
- NUS-Wide Images HOT 1
- Prompt tuning label embedding HOT 1
- Question about model, clip model HOT 1
- Provide more detail on CNN backbone HOT 1
- Dataset code for Open IMages HOT 1
- How long does the training stage take? HOT 1
- "label_emb.pt" file HOT 2
- OSError HOT 1
- Thanks for your excellent work, I would like to know how to generate this label_emb.pt
- Regarding the "nus wide" label
- Reproducing results on NUS-WIDE
- The improvement of the model's recognition performance on unseen classes.
- how to make label_emb.pt HOT 1
- files from BiAM missing. HOT 4
- Do you plan on releasing pretrained checkpoints for open images trained model?
- Training token_embedding in the second stage
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