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/4aa190e9a603743a78fc495f259bc062bd4ba99c/pytorch_model.bin
- Command line
-
hf download hf://sys2/cppe5_use_data_finetuning@4aa190e9a603743a78fc495f259bc062bd4ba99c/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sys2/cppe5_use_data_finetuning/resolve/4aa190e9a603743a78fc495f259bc062bd4ba99c/pytorch_model.bin
167 MB
- Xet hash:
- 756394fa4b99b015a7571d952ba42fda84efcea16490c46317919bf69b049238
- Size of remote file:
- 167 MB
- SHA256:
- b31875cd8209e72b88815afe199fb47c9f385542b9ad4bd9fad4dd2de01833a0
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