Instructions to use ajaye2/vit_mae_img_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ajaye2/vit_mae_img_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ajaye2/vit_mae_img_base", trust_remote_code=True, device_map="auto") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("ajaye2/vit_mae_img_base", trust_remote_code=True, dtype="auto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoModelForImageClassification
model = AutoModelForImageClassification.from_pretrained("ajaye2/vit_mae_img_base", trust_remote_code=True, dtype="auto", device_map="auto")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ajaye2/vit_mae_img_base", trust_remote_code=True, device_map="auto") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")