Instructions to use tanukinet/hanko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanukinet/hanko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="tanukinet/hanko")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("tanukinet/hanko") model = AutoModelForObjectDetection.from_pretrained("tanukinet/hanko", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from tanukinet/hanko: direct link, hf CLI and curl.
- Browser
- Download file 26 Bytes
-
https://huggingface.co/tanukinet/hanko/resolve/main/README.md
- Command line
-
hf download hf://tanukinet/hanko/README.md
-
curl -L -o README.md https://huggingface.co/tanukinet/hanko/resolve/main/README.md
26 Bytes
metadata
license: openrail