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")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ivensamdh/gender") model = AutoModelForImageClassification.from_pretrained("ivensamdh/gender", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ivensamdh/gender: direct link, hf CLI and curl.
- Browser
- Download file 86.7 MB
-
https://huggingface.co/ivensamdh/gender/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://ivensamdh/gender@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ivensamdh/gender/resolve/refs%2Fpr%2F1/pytorch_model.bin
86.7 MB
- Xet hash:
- 1373a4322b84c7de17a2f004fe8aa61205063230d36675eb957c5aab4453752d
- Size of remote file:
- 86.7 MB
- SHA256:
- 312b7db34465da70c9d169d33cdffb551fbc29baa04091b6e7a61d919df9d9d5
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