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 pytorch_model.bin from shubhamWi91/train68: direct link, hf CLI and curl.
- Browser
- Download file 243 MB
-
https://huggingface.co/shubhamWi91/train68/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shubhamWi91/train68/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shubhamWi91/train68/resolve/main/pytorch_model.bin
243 MB
- Xet hash:
- 5ea6c006147e7285e1fa33cf6f57af316e038adaa3c8a1ea36eb8ef41a842e68
- Size of remote file:
- 243 MB
- SHA256:
- 0a6055c5ab94cf39812c45d63235b7f35abea22a9d6926b0770b62838dc5707c
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