Instructions to use shubhamWi91/train57 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train57 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train57")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train57") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train57", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from shubhamWi91/train57: direct link, hf CLI and curl.
- Browser
- Download file 243 MB
-
https://huggingface.co/shubhamWi91/train57/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shubhamWi91/train57/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shubhamWi91/train57/resolve/main/pytorch_model.bin
243 MB
- Xet hash:
- 43482b3062a25e0fb6168efb0aa8265bec00b49d0559e650277622b3e871259c
- Size of remote file:
- 243 MB
- SHA256:
- bce07fd7f9f7123bdd62235894e33db0fbba39d0405867df9d4e165af533c122
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