Instructions to use gaf7921/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gaf7921/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="gaf7921/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("gaf7921/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("gaf7921/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gaf7921/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/gaf7921/cppe5_use_data_finetuning/resolve/fa1855594e047b6f5d236bd77980e72a2bcd0dbd/pytorch_model.bin
- Command line
-
hf download hf://gaf7921/cppe5_use_data_finetuning@fa1855594e047b6f5d236bd77980e72a2bcd0dbd/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gaf7921/cppe5_use_data_finetuning/resolve/fa1855594e047b6f5d236bd77980e72a2bcd0dbd/pytorch_model.bin
167 MB
- Xet hash:
- 39bc34c3b18a59dc5b71731b712d4f58a8a5e0f52ea1c2670b615bad53bf055a
- Size of remote file:
- 167 MB
- SHA256:
- ef0f87169158924b233afe0b3aead5d26dd46fc85448eb3a7031f414b3d57996
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