Instructions to use ivensamdh/gender with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivensamdh/gender with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ivensamdh/gender") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ivensamdh/gender") model = AutoModelForImageClassification.from_pretrained("ivensamdh/gender") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c51dbec37dbb72d223e2c4803749557ac9d87692cbeab29feffd4d93b36ecbb0
- Size of remote file:
- 3.52 kB
- SHA256:
- b928191cb4238855b671fbfc624eb78d15632f82a2df62fa728d99ae5fe40202
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.