Instructions to use shilpid/candy-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shilpid/candy-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="shilpid/candy-finetuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("shilpid/candy-finetuned") model = AutoModelForObjectDetection.from_pretrained("shilpid/candy-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shilpid/candy-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/shilpid/candy-finetuned/resolve/main/training_args.bin
- Command line
-
hf download hf://shilpid/candy-finetuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shilpid/candy-finetuned/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- 1a947c574b2580fa995146040860652b707afe52d7001643fb80db40e4d73ab7
- Size of remote file:
- 3.9 kB
- SHA256:
- 7aed57c63dfc5953399ea8fc81e02f1133d872d5b71a23aea0df2da6c20dfde0
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