Instructions to use shubhamWi91/train66 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train66 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train66")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train66") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train66", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shubhamWi91/train66: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/shubhamWi91/train66/resolve/main/training_args.bin
- Command line
-
hf download hf://shubhamWi91/train66/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shubhamWi91/train66/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 7504d6a1a91847b91241ea06bd29297d347d646e5a4550dce8155a460264e481
- Size of remote file:
- 4.09 kB
- SHA256:
- 8f6b96151c50be7abcd5a934e6a584253e8a145e3406363ccb1e4b74808895ec
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