Instructions to use shubhamWi91/train44 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train44 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train44")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train44") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train44", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shubhamWi91/train44: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/shubhamWi91/train44/resolve/main/training_args.bin
- Command line
-
hf download hf://shubhamWi91/train44/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shubhamWi91/train44/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- f34d403d6845e7e7d914cfa108f34b5ae28d5ec6b950c4b6945aa9f7e62c2179
- Size of remote file:
- 4.09 kB
- SHA256:
- 6001ec0b120de104dcfed966bd24258820d4c9bc981864534e8f05a64376e284
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