Instructions to use sys2/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sys2/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="sys2/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("sys2/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("sys2/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sys2/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/sys2/cppe5_use_data_finetuning/resolve/ee5ffc99dad94fc9ffdcba51ccd73ec4fb168ed9/pytorch_model.bin
- Command line
-
hf download hf://sys2/cppe5_use_data_finetuning@ee5ffc99dad94fc9ffdcba51ccd73ec4fb168ed9/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sys2/cppe5_use_data_finetuning/resolve/ee5ffc99dad94fc9ffdcba51ccd73ec4fb168ed9/pytorch_model.bin
167 MB
- Xet hash:
- e9f746196b04699551543556a2ccb7cb9a10ebac1fc4a791f9a0449de8a423bf
- Size of remote file:
- 167 MB
- SHA256:
- f75b349c149949cb47e86f347f5db224c1043cfcac0c9c71fe058568737ced76
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