Instructions to use shubhamWi91/train55 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train55 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train55")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train55") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train55", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from shubhamWi91/train55: direct link, hf CLI and curl.
- Browser
- Download file 243 MB
-
https://huggingface.co/shubhamWi91/train55/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shubhamWi91/train55/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shubhamWi91/train55/resolve/main/pytorch_model.bin
243 MB
- Xet hash:
- 1305e6c7edac8b5ec0251ffe181149395bf0c33dfe31bf8f9d38afb002e9ab1c
- Size of remote file:
- 243 MB
- SHA256:
- b3caaef1499a21f16fb3b2a3c7fb426ef7bb0bb97ae9c06b719eb8e2d63edd6a
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