Instructions to use axelit64/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use axelit64/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="axelit64/image_classification") 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("axelit64/image_classification") model = AutoModelForImageClassification.from_pretrained("axelit64/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from axelit64/image_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/axelit64/image_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://axelit64/image_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/axelit64/image_classification/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 9e1074b1aea4730acb87c255a9a22e3ccae43d85b8b93da53429c27b0d1cf2db
- Size of remote file:
- 4.09 kB
- SHA256:
- f6b212921beff142609ca18d94bc381fdc9ef33d5e09f42b3f45383fab17b7e1
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