Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
Russian
vit
huggingpics
Eval Results (legacy)
Instructions to use Poliandr/moscow-attractions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Poliandr/moscow-attractions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Poliandr/moscow-attractions") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Poliandr/moscow-attractions") model = AutoModelForImageClassification.from_pretrained("Poliandr/moscow-attractions") - Notebooks
- Google Colab
- Kaggle
moscow-attractions
Эта модель призвана распознавать картинки шести наиболее известных достопримечательностей Москвы. Модель обучена на 150 картинках для каждой достопримечательности, найденных поисковой машиной по названию.
Примеры картинок из датасета
Bolshoi Theatre
Grand Kremlin Palace
Ivan the Great Bell Tower
Lomonosov Moscow State University
Tsar Bell
Tsar Cannon
- Downloads last month
- 6
Evaluation results
- Accuracyself-reported0.656





