Instructions to use ryul99/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ryul99/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ryul99/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("ryul99/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("ryul99/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ryul99/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/ryul99/cppe5_use_data_finetuning/resolve/cf1a96dcdaa52cdbbd688559691d48fb01cf030d/pytorch_model.bin
- Command line
-
hf download hf://ryul99/cppe5_use_data_finetuning@cf1a96dcdaa52cdbbd688559691d48fb01cf030d/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ryul99/cppe5_use_data_finetuning/resolve/cf1a96dcdaa52cdbbd688559691d48fb01cf030d/pytorch_model.bin
167 MB
- Xet hash:
- 6f229ebe3866a7ca5df9054956e90f1518cea9da58448c5629c72d95a98fd9f5
- Size of remote file:
- 167 MB
- SHA256:
- 397716eb0eb995e85ac10eadc74f73239f195c79b9ec9dc316a9d51b4570a094
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