Instructions to use shubhamWi91/train58 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train58 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train58")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train58") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train58", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from shubhamWi91/train58: direct link, hf CLI and curl.
- Browser
- Download file 243 MB
-
https://huggingface.co/shubhamWi91/train58/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shubhamWi91/train58/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shubhamWi91/train58/resolve/main/pytorch_model.bin
243 MB
- Xet hash:
- cc8bd943a07b78503c2e08d6d9bfa3ac99d0557b4a6baffe2e1941d2c503e1c5
- Size of remote file:
- 243 MB
- SHA256:
- 7ffcfb7b47aa2dccfedf546f9c075708369dcaec12073cabd36c28553e6357a1
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