Instructions to use shubhamWi91/train46 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train46 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train46")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train46") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train46", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shubhamWi91/train46: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/shubhamWi91/train46/resolve/main/training_args.bin
- Command line
-
hf download hf://shubhamWi91/train46/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shubhamWi91/train46/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 310d6261a2e408046667a1063c132bbfe48d6645b3b9984965ad5326a0407e76
- Size of remote file:
- 4.09 kB
- SHA256:
- a97551d87a7d15cde85b7455513f2948d153d881c68d3a89a4650a02835c7770
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