Instructions to use shubhamWi91/train4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train4")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train4") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shubhamWi91/train4: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/shubhamWi91/train4/resolve/main/training_args.bin
- Command line
-
hf download hf://shubhamWi91/train4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shubhamWi91/train4/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 2abf83463995b3b28680588e3deec23d02e4a064706f350e80cb71b22f270f94
- Size of remote file:
- 4.09 kB
- SHA256:
- 64fb03bde5ee3c34deacdcfb5baa0910ae428b5b916c4632c9f514a54dd06af4
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