| # Pokémon Classifier | |
| # Intro | |
| A fine-tuned version of ViT-base on a collected set of Pokémon images. You can read more about the model [here](https://medium.com/@imjeffhi4/tutorial-using-vision-transformer-vit-to-create-a-pok%C3%A9mon-classifier-cb3f26ff2c20). | |
| # Using the model | |
| ```python | |
| from transformers import ViTForImageClassification, ViTFeatureExtractor | |
| from PIL import Image | |
| import torch | |
| # Loading in Model | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| model = ViTForImageClassification.from_pretrained( "imjeffhi/pokemon_classifier").to(device) | |
| feature_extractor = ViTFeatureExtractor.from_pretrained('imjeffhi/pokemon_classifier') | |
| # Caling the model on a test image | |
| img = Image.open('test.jpg') | |
| extracted = feature_extractor(images=img, return_tensors='pt').to(device) | |
| predicted_id = model(**extracted).logits.argmax(-1).item() | |
| predicted_pokemon = model.config.id2label[predicted_id] | |
| ``` |