Instructions to use PCFISH/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PCFISH/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="PCFISH/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("PCFISH/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("PCFISH/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from PCFISH/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/PCFISH/cppe5_use_data_finetuning/resolve/8e8985e4a1d0dbf8a005d1c7d5bfafedcf09c6aa/pytorch_model.bin
- Command line
-
hf download hf://PCFISH/cppe5_use_data_finetuning@8e8985e4a1d0dbf8a005d1c7d5bfafedcf09c6aa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/PCFISH/cppe5_use_data_finetuning/resolve/8e8985e4a1d0dbf8a005d1c7d5bfafedcf09c6aa/pytorch_model.bin
167 MB
- Xet hash:
- 74387d1749e0b262b4cbf7f1e4645a58fdaaa351b265ea8021b8adc2bf00a89e
- Size of remote file:
- 167 MB
- SHA256:
- 7aecc70c3f582a9d5bb3ed8e4c25f7b81d101c0be3e7897cdaa7ba41253c483e
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