Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("sanali209/sketch_filter")
model = AutoModelForImageClassification.from_pretrained("sanali209/sketch_filter", device_map="auto")Quick Links
sanali209/sketch_filter
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
- Downloads last month
- 5
Evaluation results
- Accuracyself-reported0.881
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sanali209/sketch_filter") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")