Instructions to use Deval1004/streetvision21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deval1004/streetvision21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Deval1004/streetvision21") 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("Deval1004/streetvision21") model = AutoModelForImageClassification.from_pretrained("Deval1004/streetvision21", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Deval1004/streetvision21: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/Deval1004/streetvision21/resolve/main/training_args.bin
- Command line
-
hf download hf://Deval1004/streetvision21/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Deval1004/streetvision21/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 106da7b2d4c7bf8c5427d7cb4079c91dacedf8b65f17a67b93bedd13ce7a07d6
- Size of remote file:
- 5.3 kB
- SHA256:
- 347fa148c8e382454a04d614e96abdd14ff709be94adfe135ccbbe7516e28679
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