Instructions to use lialbose/P6_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lialbose/P6_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="lialbose/P6_Model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("lialbose/P6_Model") model = AutoModelForImageClassification.from_pretrained("lialbose/P6_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from lialbose/P6_Model: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/lialbose/P6_Model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://lialbose/P6_Model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/lialbose/P6_Model/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- e3c9db3829ff5126aa3bf6b4fa2cee0e2d95bee1c89295cb4bf8539677960ee0
- Size of remote file:
- 343 MB
- SHA256:
- dc8320194d6c5b6ddc79ab64c7272fcec026fdf1c2e96bf0d481a235a753853c
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