Instructions to use Moonjunho/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Moonjunho/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Moonjunho/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Moonjunho/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("Moonjunho/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Moonjunho/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/Moonjunho/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Moonjunho/cppe5_use_data_finetuning@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Moonjunho/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/pytorch_model.bin
167 MB
- Xet hash:
- 4b59ac11167331d0f5ca0e345af1f4aa72904d8b6b8e451fc6679c9a1fa7b9dd
- Size of remote file:
- 167 MB
- SHA256:
- 651d6953e4ffa6039da572f2bca97fc40c1e6fb6a4101ad7f92b89bdf79fab44
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