Instructions to use akar49/only-crack-I with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akar49/only-crack-I with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="akar49/only-crack-I")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("akar49/only-crack-I") model = AutoModelForObjectDetection.from_pretrained("akar49/only-crack-I", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from akar49/only-crack-I: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/akar49/only-crack-I/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://akar49/only-crack-I@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/akar49/only-crack-I/resolve/refs%2Fpr%2F1/training_args.bin
3.96 kB
- Xet hash:
- decf18631824082351b38fab42ed6a3a6b8e55be82c3e8972269d79bfb6fcffd
- Size of remote file:
- 3.96 kB
- SHA256:
- 11dbceb2f12c22893c90195d628d9edb06cd386680fe18d0e86ee45b582ddfd2
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