Instructions to use ahmedesmail16/Project_Class_Aug_Model_vit-large-patch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedesmail16/Project_Class_Aug_Model_vit-large-patch16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahmedesmail16/Project_Class_Aug_Model_vit-large-patch16") 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("ahmedesmail16/Project_Class_Aug_Model_vit-large-patch16") model = AutoModelForImageClassification.from_pretrained("ahmedesmail16/Project_Class_Aug_Model_vit-large-patch16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from ahmedesmail16/Project_Class_Aug_Model_vit-large-patch16: direct link, hf CLI and curl.
- Browser
- Download file 1.21 GB
-
https://huggingface.co/ahmedesmail16/Project_Class_Aug_Model_vit-large-patch16/resolve/main/model.safetensors
- Command line
-
hf download hf://ahmedesmail16/Project_Class_Aug_Model_vit-large-patch16/model.safetensors
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curl -L -o model.safetensors https://huggingface.co/ahmedesmail16/Project_Class_Aug_Model_vit-large-patch16/resolve/main/model.safetensors
1.21 GB
- Xet hash:
- 9def04d1bc36fed8f6e84601c5e8377bac209ce0361372c6764cd3d0d80965f5
- Size of remote file:
- 1.21 GB
- SHA256:
- d46357e07766dc41488c2ea7ae0963141731a1afd544d9470d2d9529e10a3e6c
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