Instructions to use ahmedesmail16/Project_Class_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_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_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_Model_vit-large-patch16") model = AutoModelForImageClassification.from_pretrained("ahmedesmail16/Project_Class_Model_vit-large-patch16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ahmedesmail16/Project_Class_Model_vit-large-patch16: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/ahmedesmail16/Project_Class_Model_vit-large-patch16/resolve/main/training_args.bin
- Command line
-
hf download hf://ahmedesmail16/Project_Class_Model_vit-large-patch16/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ahmedesmail16/Project_Class_Model_vit-large-patch16/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- cbaa5be9f17aaec04afcc0ec7bcf438f691e3bd1c48167a62a951173b44ccc76
- Size of remote file:
- 4.92 kB
- SHA256:
- 38ddc104be8c26c7dba51db1f64f616e3f88ad3f6d94f53381cfdfe0678dd13a
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