Comments (4)
Hi Yikai,
Selecting 50 concepts using this codebase is very fast if you have precomputed all the features. But I will also provide the selected concepts using all training data in the repo shortly.
Yue
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Sorry for the late reply, please see the data here: https://github.com/YueYANG1996/LaBo/tree/main/selected_concepts
from labo.
Hi Yue, thanks a lot for providing the selected concepts! Could you also provide the instructions on how to generate the selected concepts at the Readme? It would be very helpful for us to run this procedure on other datasets.
from labo.
Hi Yue, thanks a lot for providing the selected concepts! Could you also provide the instructions on how to generate the selected concepts at the Readme? It would be very helpful for us to run this procedure on other datasets.
Please check here for this question.
from labo.
Related Issues (20)
- Packages are not available from current channels HOT 2
- cant train with the dataset cifar10 and cifar100 HOT 4
- Query regarding selecting concept in Figure 7 HOT 1
- concept generation for custom dataset HOT 1
- code for interpretation HOT 2
- conda: fail to install the environment HOT 3
- Cifar10 & cifar100 datasets problem HOT 2
- main.py: error: argument --func: expected one argument HOT 1
- sh labo_train.sh {DATASET} {SHOTS} does not match labo_train.sh HOT 1
- the unuse of use_img_norm and use_txt_norm HOT 4
- Unexpected CIFAR10 Results HOT 2
- The code for generating the initial concepts HOT 3
- TypeError: __new__() missing 1 required positional argument: 'task' HOT 5
- Problem related to high LaBO training time HOT 1
- GPU for LaBo HOT 2
- I want to test the accuracy of a specific class. How do I know which number represents said class? HOT 1
- Requirement Text Installation Issue HOT 2
- Theoretical proof of submodular function
- inference_code HOT 2
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