Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use 019100385b/SitiosTuristicosyArqueologicosCusco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 019100385b/SitiosTuristicosyArqueologicosCusco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="019100385b/SitiosTuristicosyArqueologicosCusco") 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("019100385b/SitiosTuristicosyArqueologicosCusco") model = AutoModelForImageClassification.from_pretrained("019100385b/SitiosTuristicosyArqueologicosCusco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
SitiosTuristicosyArqueologicosCusco
Autogenerated by HuggingPics๐ค๐ผ๏ธ
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
BarrioSanBlas
CatedralDelCusco
CristoBlanco
IglesiaLaMerced
LagunaHumantay
MachuPicchu
Maras
Moray
Piedra12Angulos
Pikillacta
PlazaDeArmas
Qenqo
Qorikancha
Raqchi
Sacsayhuaman
Sapantiana
TemploAndahuaylillas
Tipon
ValleRojo
Vinicunca
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Evaluation results
- Accuracyself-reported0.989



















