YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/model-cards#model-card-metadata)
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.
Using the model
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]
- Downloads last month
- 289
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.