Instructions to use unojcn9f/screenlist-slicing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unojcn9f/screenlist-slicing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="unojcn9f/screenlist-slicing")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("unojcn9f/screenlist-slicing") model = AutoModelForObjectDetection.from_pretrained("unojcn9f/screenlist-slicing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from unojcn9f/screenlist-slicing: direct link, hf CLI and curl.
- Browser
- Download file 155 Bytes
-
https://huggingface.co/unojcn9f/screenlist-slicing/resolve/main/README.md
- Command line
-
hf download hf://unojcn9f/screenlist-slicing/README.md
-
curl -L -o README.md https://huggingface.co/unojcn9f/screenlist-slicing/resolve/main/README.md
155 Bytes
metadata
license: agpl-3.0
widget:
- src: >-
https://huggingface.co/unojcn9f/screenlist-slicing/resolve/main/big-buck-bunny.png
example_title: Big Buck Bunny