Instructions to use SeoJunn/hyuningface with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SeoJunn/hyuningface with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="SeoJunn/hyuningface")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("SeoJunn/hyuningface") model = AutoModelForObjectDetection.from_pretrained("SeoJunn/hyuningface", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SeoJunn/hyuningface: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/SeoJunn/hyuningface/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SeoJunn/hyuningface/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SeoJunn/hyuningface/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 9090a20d4c0aafe0ca965bba650e5a819b617d3eb212389f4b5f9ad8b76d703c
- Size of remote file:
- 167 MB
- SHA256:
- 57e069e7b601f88c77d3051a16527b1bafa0fde0329adf8cfa1d98f0ca90775c
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