Instructions to use shubhamWi91/train52 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train52 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train52")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train52") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train52", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shubhamWi91/train52: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/shubhamWi91/train52/resolve/main/training_args.bin
- Command line
-
hf download hf://shubhamWi91/train52/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shubhamWi91/train52/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 3547d889487f0de268e880ba6e3eb6f653b796c399173c81d84e2ade702bae7e
- Size of remote file:
- 4.09 kB
- SHA256:
- c7877a787715d549ea2e83975c1d1c1f22153d6d224124d366ac22c5db9681de
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