Image Classification
Transformers
Safetensors
English
metaclip_2
text-generation-inference
gender-identifier
Instructions to use prithivMLmods/MetaCLIP-2-Gender-Identifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/MetaCLIP-2-Gender-Identifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/MetaCLIP-2-Gender-Identifier") 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/MetaCLIP-2-Gender-Identifier") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/MetaCLIP-2-Gender-Identifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c79bbd3bb2c5d952c41cab84c07b41d5533ff229fe95faab934fe6dac163d3f5
- Size of remote file:
- 1.47 kB
- SHA256:
- cf6de35015d83495745d5edb65945334b61449cd6c3e3a66b09078c5823a4a26
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.