Instructions to use limehee/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use limehee/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="limehee/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("limehee/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("limehee/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from limehee/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/limehee/cppe5_use_data_finetuning/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://limehee/cppe5_use_data_finetuning/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/limehee/cppe5_use_data_finetuning/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- fe796839103038a0fdb055ba0a9deb8428837fdc84acbd05a098b29ff2c4c0c9
- Size of remote file:
- 167 MB
- SHA256:
- ef21b128d32c2b6261967b9dd4fa1fca53fed89a3729178b9dd514e20067bc7f
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