Instructions to use siois/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use siois/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="siois/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("siois/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("siois/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from siois/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/siois/cppe5_use_data_finetuning/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://siois/cppe5_use_data_finetuning/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/siois/cppe5_use_data_finetuning/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- e6dfcb18b542d619e58e6cca8090f52fa24272c0189e59ebd368698e2d3ecae1
- Size of remote file:
- 167 MB
- SHA256:
- 7668d2375940f22b9dd98ee63c5459ccab05336e28261a76c5e0ce1470cbee3a
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