Closed czczup closed 1 year ago
As far as I know, I should run clip inference first, like this:
clip-retrieval inference --input_dataset ./data --output_folder ./data_embeddings --clip_model "open_clip:xlm-roberta-base-ViT-B-32"
Is there any way I can load my own finetuned weights here?
Maybe I should modify some code to load my weights.
Hello there! I'm currently attempting to execute the end-to-end clip retrieval utilizing a finetuned checkpoint of openclip/xlm-roberta-base-vitb32. However, I'm encountering unusual outcomes on the frontend page. Did you encounter any bugs in the code or face similar challenges that you could provide insights on or recommend how to address?
hello how do you load your finetuned weights?
Thanks for your awesome work!
I use the open-clip model ('xlm-roberta-base-ViT-B-32', 'laion5b_s13b_b90k') as initialization, and fine-tune the model on my custom image-text dataset.
After that, I got many checkpoints like
open_clip/work_dirs/2023_07_24-23_01_12-model_xlm-roberta-base-ViT-B-32-lr_1e-05-b_512-j_8-p_amp/checkpoints/epoch_30.pt
. How can I use this model to build a retrieval backend.