Instructions to use shubhamWi91/train49 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train49 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train49")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train49") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train49", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shubhamWi91/train49: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/shubhamWi91/train49/resolve/main/training_args.bin
- Command line
-
hf download hf://shubhamWi91/train49/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shubhamWi91/train49/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 03f0ccbee2e6f7089e6bb36256dd18a9873379d67e327d0b95aacf35e0deada1
- Size of remote file:
- 4.09 kB
- SHA256:
- b21b09b18a33010b52691987dbc82bea21e23fcc7df937b4760bf2439bde9911
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