Instructions to use shubhamWi91/train69 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train69 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train69")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train69") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train69", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from shubhamWi91/train69: direct link, hf CLI and curl.
- Browser
- Download file 243 MB
-
https://huggingface.co/shubhamWi91/train69/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shubhamWi91/train69/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shubhamWi91/train69/resolve/main/pytorch_model.bin
243 MB
- Xet hash:
- d380b44370539ce0dd08416c7c4a2fdb393949e710eba8488aaa0678fa43fb90
- Size of remote file:
- 243 MB
- SHA256:
- 2b3a702f714c1428adf59cdf38d0ea03a75cd4407b36ce4acb4324043ba6f57e
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