Instructions to use LeeRuben/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeeRuben/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="LeeRuben/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("LeeRuben/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("LeeRuben/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from LeeRuben/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/LeeRuben/cppe5_use_data_finetuning/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://LeeRuben/cppe5_use_data_finetuning/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/LeeRuben/cppe5_use_data_finetuning/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- c6c25a3e78909e10699d23d6016bbcf70c90fdbb1e930131fa0a9fe41dad974f
- Size of remote file:
- 167 MB
- SHA256:
- e3ddd76f0b716eeee520feccbe1dbd8a88512374d9281988549ac04b9a79a970
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