Dear-Acanthisitta698
Dear-Acanthisitta698 t1_j4zqkv8 wrote
Text QA might work. Give descriptiom as passage and question as "how many number of rooms in this house?".
Dear-Acanthisitta698 t1_ityuwcv wrote
I like pudb with classic blue screen
Dear-Acanthisitta698 t1_ittlyp3 wrote
May use embedding for categorical value and linear for continuous value. You can also use bin for making continuous value into categorical.
Dear-Acanthisitta698 t1_itpqu2j wrote
Reply to comment by External_Oven_6379 in Combining image and text embedding [P] by External_Oven_6379
I think the problem is concatenating visual and text feature. While dim of text feature is a lot smaller than visual feature, these information might be white out. So you may following LastVariation 's ideas (first get images with same categories then search within them) or scale up the text vector (maybe multiply 80, this is a hyperparmeter).
Dear-Acanthisitta698 t1_itpckwk wrote
I suggest using recent pretrained models to extract features. Open AI Clip might be your start point.
Dear-Acanthisitta698 t1_itjt7mg wrote
If you save optimizer as well then it will almost same (it is almot same because random functions e.g. dropout will have different value). If you does not save the optimizer, then it will use initial lr setting so it might results different.
Dear-Acanthisitta698 t1_ir4rpk8 wrote
Reply to [R] Google Colab alternative by Zatania
Maybe using numpy instead of python list can help
Dear-Acanthisitta698 t1_j70f4rk wrote
Reply to [p] Is it possible to add more classes to an already trained resnet image classifier model without the need to retrain it in all dataset again? [p] by YukkiiCode
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