Instructions to use AlexLien/trained_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlexLien/trained_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="AlexLien/trained_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("AlexLien/trained_model") model = AutoModelForObjectDetection.from_pretrained("AlexLien/trained_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AlexLien/trained_model: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/AlexLien/trained_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AlexLien/trained_model/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/AlexLien/trained_model/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- dbde19fcc5b698f89976a49076caaf34bae670c26cd35d20f87109571c724dd8
- Size of remote file:
- 167 MB
- SHA256:
- ab649895ed6965372e72ad291472f136451f392746d09b93a98ed95a11307e0b
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