Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use jonassvatos/fdasda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonassvatos/fdasda with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jonassvatos/fdasda") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("jonassvatos/fdasda") model = AutoModelForImageClassification.from_pretrained("jonassvatos/fdasda", device_map="auto") - Notebooks
- Google Colab
- Kaggle
fdasda
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
black and white image
low contrast image
rotated image
skewed scan
torn paper
- Downloads last month
- 5
Evaluation results
- Accuracyself-reported0.741




