Instructions to use AmineAllo/margin-element-detector-fm-sandy-dragon-14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmineAllo/margin-element-detector-fm-sandy-dragon-14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="AmineAllo/margin-element-detector-fm-sandy-dragon-14")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("AmineAllo/margin-element-detector-fm-sandy-dragon-14") model = AutoModelForObjectDetection.from_pretrained("AmineAllo/margin-element-detector-fm-sandy-dragon-14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AmineAllo/margin-element-detector-fm-sandy-dragon-14: direct link, hf CLI and curl.
- Browser
- Download file 115 MB
-
https://huggingface.co/AmineAllo/margin-element-detector-fm-sandy-dragon-14/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AmineAllo/margin-element-detector-fm-sandy-dragon-14/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AmineAllo/margin-element-detector-fm-sandy-dragon-14/resolve/main/pytorch_model.bin
115 MB
- Xet hash:
- e42cd3ed0ae09323014bde00f6d3bbf71db1dfd394b5044cf803f1b77a22ccbf
- Size of remote file:
- 115 MB
- SHA256:
- f77e68cc9f441f71e09599ad413580acc56e9950ff5ce76dfc76e442cfd42714
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