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/2a66ca45cfa2aeec6f8083c4024deed704cece84/pytorch_model.bin
- Command line
-
hf download hf://ryul99/cppe5_use_data_finetuning@2a66ca45cfa2aeec6f8083c4024deed704cece84/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ryul99/cppe5_use_data_finetuning/resolve/2a66ca45cfa2aeec6f8083c4024deed704cece84/pytorch_model.bin
167 MB
- Xet hash:
- 1261349cd78166604971c3cdbe811d7fa2fff59038f7f6ebc5336230632edbef
- Size of remote file:
- 167 MB
- SHA256:
- 600354b06d9f63a9036cb54bcb0a5801609346f862bec2e09114422c08723175
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