Instructions to use shubhamWi91/train54 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shubhamWi91/train54 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shubhamWi91/train54")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shubhamWi91/train54") model = AutoModelForObjectDetection.from_pretrained("shubhamWi91/train54", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from shubhamWi91/train54: direct link, hf CLI and curl.
- Browser
- Download file 243 MB
-
https://huggingface.co/shubhamWi91/train54/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shubhamWi91/train54/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shubhamWi91/train54/resolve/main/pytorch_model.bin
243 MB
- Xet hash:
- 2a370aad4c271c500eb71cd48a0875251a83ba193ff4f0a419529df79ee241d6
- Size of remote file:
- 243 MB
- SHA256:
- f5ec35d8c0d0ad53c3fb982dbf5c627edc65f73caca0378c17776c068100cddb
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