Instructions to use shubhamWi91/train59 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train59 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train59")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train59") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train59", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from shubhamWi91/train59: direct link, hf CLI and curl.
- Browser
- Download file 243 MB
-
https://huggingface.co/shubhamWi91/train59/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shubhamWi91/train59/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shubhamWi91/train59/resolve/main/pytorch_model.bin
243 MB
- Xet hash:
- 06fffa6e91d953cd32caa0436010cfafa146af9cf9d3a86bd59cc9782f009640
- Size of remote file:
- 243 MB
- SHA256:
- b6d5bd0ac1b91548c2967a0968ccdf9b626d98a70eab15d94468235b5b7bffbb
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