Instructions to use dia218/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dia218/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="dia218/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("dia218/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("dia218/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dia218/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/dia218/cppe5_use_data_finetuning/resolve/4e6920aefbb40ad43deeccc39fdf74bc83235fb5/pytorch_model.bin
- Command line
-
hf download hf://dia218/cppe5_use_data_finetuning@4e6920aefbb40ad43deeccc39fdf74bc83235fb5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dia218/cppe5_use_data_finetuning/resolve/4e6920aefbb40ad43deeccc39fdf74bc83235fb5/pytorch_model.bin
167 MB
- Xet hash:
- 83936fa9d1a243a84b868d0841f8738acd5fe6a20f3b4ce058a078d37ca63b6e
- Size of remote file:
- 167 MB
- SHA256:
- cc324ab719b8215dfe88974701492d9dc2fd1bf9fef570ea0342f0c4d76163fe
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