Instructions to use mj124/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mj124/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="mj124/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("mj124/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("mj124/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mj124/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/mj124/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://mj124/cppe5_use_data_finetuning@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mj124/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/pytorch_model.bin
167 MB
- Xet hash:
- c0e8ba96b8906cf2c435e3574918ef988dfc90a55370bda15b76fb67a4da40c0
- Size of remote file:
- 167 MB
- SHA256:
- 7f29f3b9870f5c4373222f8bf4a332d5a477f56d53fc6d9472203dc1707ce44c
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