Instructions to use Giuliano/places with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Giuliano/places with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Giuliano/places") 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("Giuliano/places") model = AutoModelForImageClassification.from_pretrained("Giuliano/places", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Giuliano/places: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/Giuliano/places/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Giuliano/places/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Giuliano/places/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 6f9c85b2aad79677dd547722a7e02a111bbb1d1e5adfa0830e865cd256ae4b30
- Size of remote file:
- 343 MB
- SHA256:
- 997c00b73ef3a0f1007f9d0350cd9e7a7d19da5543162693653c7327289e8179
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