Instructions to use hamaadayubkhan/NuttriScan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hamaadayubkhan/NuttriScan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hamaadayubkhan/NuttriScan") 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("hamaadayubkhan/NuttriScan") model = AutoModelForImageClassification.from_pretrained("hamaadayubkhan/NuttriScan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hamaadayubkhan/NuttriScan: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/hamaadayubkhan/NuttriScan/resolve/main/training_args.bin
- Command line
-
hf download hf://hamaadayubkhan/NuttriScan/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hamaadayubkhan/NuttriScan/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- a408a32e001c5ed67d2093554641534a7531a8c283aded74fd76639eee5f9547
- Size of remote file:
- 5.24 kB
- SHA256:
- f27bcb724f4ecdf37dde3dc76e1ef6cf762f306bee11c03c88b7487309285236
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