Instructions to use taohungchang/candy_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taohungchang/candy_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="taohungchang/candy_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("taohungchang/candy_model") model = AutoModelForObjectDetection.from_pretrained("taohungchang/candy_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from taohungchang/candy_model: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/taohungchang/candy_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://taohungchang/candy_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/taohungchang/candy_model/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 046482e59ac21557e2a86beeabb2ea9b23ce060371bcdf7de0582d61675c4b05
- Size of remote file:
- 167 MB
- SHA256:
- 65255c9a969e7a479ced260444f064f8b4b3a2d65f32ef20c975c7f93e23b222
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