Instructions to use OhST/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OhST/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="OhST/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("OhST/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("OhST/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from OhST/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/OhST/cppe5_use_data_finetuning/resolve/5f48ee4089c150f49dcda1f52de3e7d54fb559ff/pytorch_model.bin
- Command line
-
hf download hf://OhST/cppe5_use_data_finetuning@5f48ee4089c150f49dcda1f52de3e7d54fb559ff/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/OhST/cppe5_use_data_finetuning/resolve/5f48ee4089c150f49dcda1f52de3e7d54fb559ff/pytorch_model.bin
167 MB
- Xet hash:
- 48bf954027c12eb7774f2218e1b16f038516e6ec9b6cd85a6ca9be8dd790928c
- Size of remote file:
- 167 MB
- SHA256:
- a3ba3800e9f1bcbf4e662102d98d164a073435706d95ff5ef277b4d980529349
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