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 training_args.bin from AmineAllo/margin-element-detector-fm-sandy-dragon-14: direct link, hf CLI and curl.
- Browser
- Download file 4.47 kB
-
https://huggingface.co/AmineAllo/margin-element-detector-fm-sandy-dragon-14/resolve/main/training_args.bin
- Command line
-
hf download hf://AmineAllo/margin-element-detector-fm-sandy-dragon-14/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AmineAllo/margin-element-detector-fm-sandy-dragon-14/resolve/main/training_args.bin
4.47 kB
- Xet hash:
- eb4e2954b6aa23c7ec0257292b01d27652e78098e9f8fc5fa17417825440b575
- Size of remote file:
- 4.47 kB
- SHA256:
- 1a9300a898464f0950b7dd15b5de30f7c616f3fbd7bd959bacbd2ced97a228a2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.