Instructions to use AkremGomri/hf_image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AkremGomri/hf_image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AkremGomri/hf_image_classification") 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("AkremGomri/hf_image_classification") model = AutoModelForImageClassification.from_pretrained("AkremGomri/hf_image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AkremGomri/hf_image_classification: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/AkremGomri/hf_image_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://AkremGomri/hf_image_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AkremGomri/hf_image_classification/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- 5b8b247f4e00c550efc2a5354916d8ee25ba1e9cd9b5c78e1329070fd2b8a244
- Size of remote file:
- 5.2 kB
- SHA256:
- 0f9cd7c4047820de56c212160363d968aa04a78267372111a1cd90671bb30ba2
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