# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("TheBirdLegacy/CatsandDogsPOC-Swin")
model = AutoModelForImageClassification.from_pretrained("TheBirdLegacy/CatsandDogsPOC-Swin", device_map="auto")Quick Links
Resnet is more lightweight but this is better in terms of loss, at the cost of being 3.5X the size.
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 2540477801
- CO2 Emissions (in grams): 1.1656
Validation Metrics
- Loss: 0.000
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000
- Downloads last month
- 4
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TheBirdLegacy/CatsandDogsPOC-Swin") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")