Improve model card and add metadata
Hi! I'm Niels from the Hugging Face community team. This PR improves your model card by:
- Adding the
image-to-imagepipeline tag to the metadata for better discoverability. - Linking the model to the original paper Spanning the Visual Analogy Space with a Weight Basis of LoRAs.
- Adding a sample usage section based on your GitHub README to show users how to run inference.
- Cleaning up the links to the GitHub repository and project page.
Please review and merge if this looks good to you!
The solution does not generate image transformation as claimed by the author. Requesting to post a spaces demo page to prove this claim wrong
Hi @Rohan-97 , this model was re-trained on non-NVIDIA resources, so it does not produce the exact images from the paper, however it should perform equivalently.
For example, running this model with the following commands (with the eval data decoded) produces the images in the samples directory.
python inference.py -w "lorweb_model/lorweb_model.safetensors" -c "config.yaml" -a
"data/original/unsplash_animals/alvan-nee-brFsZ7qszSY-unsplash.jpg" -t "data/decoded_random_inference_set/db_not_in_trainset/animals/Give_this_animal_a_fantastical_set_of_armor/alvan-nee-brFsZ7qszSY-unsplash_2.png" -b "data/original/unsplash_animals/ryan-walton-AbNO2iejoXA-unsplash.jpg" -o "samples/armor_doggy.jpg" -p "Give this animal a fantastical set of armor"
python inference.py -w "lorweb_model/lorweb_model.safetensors" -c "config.yaml" -a "data/original/unsplash_persons_cropped/masoud-mostafaei-YZfxKBCze_c-unsplash.jpg" -t "data/decoded_random_inference_set/db_not_in_trainset_loras/persons/clay_toy/masoud-mostafaei-YZfxKBCze_c-unsplash_2.png" -b "data/original/unsplash_persons_cropped/oana-valeria-serban-NNSz7P1ECT4-unsplash.jpg" -o "samples/clay_woman_man.jpg" -p "Turn this image into the Clay_Toy style."
python inference.py -w "lorweb_model/lorweb_model.safetensors" -c "config.yaml" -a "data/original/unsplash_animals/aarn-giri-3lGi0BXJ1W0-unsplash.jpg" -t "data/decoded_random_inference_set/db_not_in_trainset_loras/animals/ghibli/aarn-giri-3lGi0BXJ1W0-unsplash_2.png" -b "data/original/unsplash_animals/timo-volz-ZlFKIG6dApg-unsplash.jpg" -o "samples/ghibli_animals_8.jpg" -p "Turn this image into the Ghibli style"
python inference.py -w "lorweb_model/lorweb_model.safetensors" -c "config.yaml" -a "data/original/unsplash_objects/johann-siemens-EPy0gBJzzZU-unsplash.jpg" -t "data/decoded_random_inference_set/db_not_in_trainset/objects/Turn_this_photo_into_an_architectural_rendering/johann-siemens-EPy0gBJzzZU-unsplash_2.png" -b "data/original/unsplash_objects/gustavo-S-W9vDL5whU-unsplash.jpg" -o "samples/architectural_tree_car.jpg" -p "Turn this photo into an architectural rendering"
To make sure we're aligned, I'm attaching here the input images and the results to reproduce this (the first 2 for brevitiy).
Please let me know if you still have trouble reproducing these results :)
data/original/unsplash_animals/alvan-nee-brFsZ7qszSY-unsplash.jpg
"data/decoded_random_inference_set/db_not_in_trainset/animals/Give_this_animal_a_fantastical_set_of_armor/alvan-nee-brFsZ7qszSY-unsplash_2.png"
"data/original/unsplash_animals/ryan-walton-AbNO2iejoXA-unsplash.jpg"
results
"data/original/unsplash_persons_cropped/masoud-mostafaei-YZfxKBCze_c-unsplash.jpg"
"data/decoded_random_inference_set/db_not_in_trainset_loras/persons/clay_toy/masoud-mostafaei-YZfxKBCze_c-unsplash_2.png"
"data/original/unsplash_persons_cropped/oana-valeria-serban-NNSz7P1ECT4-unsplash.jpg"
results