Comments (1)
We don't have plans to do this. In our experiment, We find it difficult to train Vit-B/32 model with an improved accuracy on ImageNet-S zero-shot classification. We only observe improvement in ViT-B/16, ViT-L/14, ViT-L/14@336 as the absolute improvement also increase with model capacity and resolution, which is interesting, but not surprising. So, we suggest using as big model as you can to test both Alpha-CLIP and original CLIP.
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Related Issues (20)
- AttributeError: 'NoneType' object has no attribute 'from_pretrained' HOT 1
- The Alpha-clip demo with LLAVA will constantly repeat a sentence under certain specific images. HOT 2
- ViT-H/14 Model HOT 2
- Encoding Images with Alpha Channel? HOT 6
- Question: Can you provide some guidance for finetuning MLLM with alpha-clip vision encoder? HOT 2
- Will you provide code for the data generation process? HOT 2
- What data enhancements were used in AlphaCLIP? HOT 3
- Could you release the code of integrating blip2 with alpha clip? HOT 4
- The magic number of 1.9231 and 6 HOT 2
- Annotations of the generated Imagenet HOT 2
- Do you consider trying Alpha-DINOv2? HOT 1
- Do you have plans to release the training code based on openclip? HOT 1
- can you provided the mask of Imagenet ? HOT 1
- Table 6: Performance of Alpha-CLIP in region level captioning HOT 1
- Poor performance on COCO dataset.
- Fail to download clip_l14_grit+mim_fultune_6xe.pth HOT 2
- Demo error HOT 5
- AhphaCLIP with llm Demo error HOT 2
- when will release alphaclip with ViT-H/14 HOT 1
- Captions in GRIT HOT 1
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