Instructions to use ivensamdh/beit_base_fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivensamdh/beit_base_fp16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ivensamdh/beit_base_fp16") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ivensamdh/beit_base_fp16") model = AutoModelForImageClassification.from_pretrained("ivensamdh/beit_base_fp16") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a72a4dcf870e26ceee0beb754e36cd5a42963461b73196705fb8ec0149d6c3b3
- Size of remote file:
- 347 MB
- SHA256:
- bfed2af60c9c612833cf9ddbaead1a435b88b6e17a348d41171d1a7b6b3a1acb
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