Instructions to use ssangttuce/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ssangttuce/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ssangttuce/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("ssangttuce/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("ssangttuce/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ssangttuce/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/ssangttuce/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://ssangttuce/cppe5_use_data_finetuning@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ssangttuce/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/pytorch_model.bin
167 MB
- Xet hash:
- 2255d5ba2996c8df53eb64211a598a78b471fcc6442f648ca23df3b1430662b3
- Size of remote file:
- 167 MB
- SHA256:
- dc6db79e6bbcb4802970bbc0044169334b2846b5ca4b390380176ca379a09604
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