Instructions to use MonasticAcademy/posture_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MonasticAcademy/posture_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MonasticAcademy/posture_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("MonasticAcademy/posture_model") model = AutoModelForImageClassification.from_pretrained("MonasticAcademy/posture_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MonasticAcademy/posture_model: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/MonasticAcademy/posture_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://MonasticAcademy/posture_model@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MonasticAcademy/posture_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
343 MB
- Xet hash:
- 88a61b436a89c85f63fac0236a48bbd8b5b9c48ba37d6abfd71233be6e6bfea9
- Size of remote file:
- 343 MB
- SHA256:
- d9d3a9ab2f0cd5747abe8bfdb85749b253481c24ab61645468b38a23b567dfc0
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