Instructions to use jeemsterri/flower_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jeemsterri/flower_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jeemsterri/flower_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("jeemsterri/flower_classification") model = AutoModelForImageClassification.from_pretrained("jeemsterri/flower_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jeemsterri/flower_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/jeemsterri/flower_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://jeemsterri/flower_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jeemsterri/flower_classification/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 76570869adecd68b140fb1e8249ca259dc33d5facace00ffdd1776e7fcd30292
- Size of remote file:
- 4.86 kB
- SHA256:
- b6b16456c79933af97eae8a1fe3bdd595a78222bb7103e4423bd83bac0c42324
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