Instructions to use prithivMLmods/Gender-Classifier-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Gender-Classifier-Mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Gender-Classifier-Mini") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Gender-Classifier-Mini") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Gender-Classifier-Mini", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 070ef3b30a91cf6813db9134e9061b832ddb7ddf27932ddd0065a73969c62444
- Size of remote file:
- 687 MB
- SHA256:
- ca2c61bce314c08c2c635e0305545daff08656f2025c9347f009aa9877b246e3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.