Instructions to use zerojun/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zerojun/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="zerojun/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("zerojun/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("zerojun/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from zerojun/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/zerojun/cppe5_use_data_finetuning/resolve/e98f1dc5287df554a9424119472363e09102bfb7/pytorch_model.bin
- Command line
-
hf download hf://zerojun/cppe5_use_data_finetuning@e98f1dc5287df554a9424119472363e09102bfb7/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zerojun/cppe5_use_data_finetuning/resolve/e98f1dc5287df554a9424119472363e09102bfb7/pytorch_model.bin
167 MB
- Xet hash:
- adca5edf555004c7860a5b27c7e6ae0e2bbaae5e81eb58d75834d88eed437648
- Size of remote file:
- 167 MB
- SHA256:
- 549a3ed5eb207b1c220c4e3f6eb18f48f7d89c7ed53089407806f9e5c58b0e74
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