Instructions to use dima806/beard_face_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/beard_face_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/beard_face_image_detection") 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("dima806/beard_face_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/beard_face_image_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-40/optimizer.pt from dima806/beard_face_image_detection: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/dima806/beard_face_image_detection/resolve/main/checkpoint-40/optimizer.pt
- Command line
-
hf download hf://dima806/beard_face_image_detection/checkpoint-40/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/dima806/beard_face_image_detection/resolve/main/checkpoint-40/optimizer.pt
687 MB
- Xet hash:
- c712a6a165a68c3ffa57645c58d48bfbca9f1ef97022097d5eed9caac16aba9f
- Size of remote file:
- 687 MB
- SHA256:
- 163d62d63d672d3b643074cef4064a9eee92d536d728ea62f6b45e41d0205454
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