Instructions to use shubhamWi91/train82 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train82 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train82")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForObjectDetection model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train82", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shubhamWi91/train82: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/shubhamWi91/train82/resolve/main/training_args.bin
- Command line
-
hf download hf://shubhamWi91/train82/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shubhamWi91/train82/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 564055d4acaf376ed63cadca46ed9abebfca28ffb600f69213f04eb6cbd3dba5
- Size of remote file:
- 4.09 kB
- SHA256:
- 7009dda25d20ccd36585c8d209ef88e620104d7a829f1d9e340015ac6e3e731a
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