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/ff3aff62f0a1542e3ec8d85cb8ecd9ec5fa86f3e/pytorch_model.bin
- Command line
-
hf download hf://OhST/cppe5_use_data_finetuning@ff3aff62f0a1542e3ec8d85cb8ecd9ec5fa86f3e/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/OhST/cppe5_use_data_finetuning/resolve/ff3aff62f0a1542e3ec8d85cb8ecd9ec5fa86f3e/pytorch_model.bin
167 MB
- Xet hash:
- 24d1a06fc518e3885d48c361f9035ccd038158b1f5f37cbff817c59d33f452a4
- Size of remote file:
- 167 MB
- SHA256:
- ca350da6d881b272ae24cc1c8c1489c5d20776cd91a80dbed00741ffaeb8bc51
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