Instructions to use shubhamWi91/train3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train3")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train3") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shubhamWi91/train3: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/shubhamWi91/train3/resolve/main/training_args.bin
- Command line
-
hf download hf://shubhamWi91/train3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shubhamWi91/train3/resolve/main/training_args.bin
4.22 kB
- Xet hash:
- 8ff46d3129147bce97bf6656ce58d397501600f8dbb60b5a03afb70c4d5670f2
- Size of remote file:
- 4.22 kB
- SHA256:
- cee27b3f73e497a907884346f1fd6f355ef41b1b74150ae317c0ebdb3d0f1053
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