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/b12f89df6db5e89e997748339e2c2e992b3ed040/pytorch_model.bin
- Command line
-
hf download hf://PCFISH/cppe5_use_data_finetuning@b12f89df6db5e89e997748339e2c2e992b3ed040/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/PCFISH/cppe5_use_data_finetuning/resolve/b12f89df6db5e89e997748339e2c2e992b3ed040/pytorch_model.bin
167 MB
- Xet hash:
- 4cecac2c372c7a690972e8f5907f5c8631c39245f72c6e13d82ac1921c0d375c
- Size of remote file:
- 167 MB
- SHA256:
- 1ac26d9d058707a9f6ffae683a25316d323eac8ebcb164c5a49cb4149a739c5a
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