Instructions to use shubhamWi91/train68 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train68 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train68")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train68") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train68", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shubhamWi91/train68: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/shubhamWi91/train68/resolve/main/training_args.bin
- Command line
-
hf download hf://shubhamWi91/train68/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shubhamWi91/train68/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 3c0dc786de6ab4d26b7fe6cece514dc9fb9920230b9932cb42d372fb0f420859
- Size of remote file:
- 4.09 kB
- SHA256:
- d68277c25cd29ba4d0b0857477bacbabeb01be0fb878a41d327fd551c1f5444b
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