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:
- 2ab82610913d004a78da706e6d013c5a272b3986d8c3c64d3204d49911d3c04a
- Size of remote file:
- 14.6 kB
- SHA256:
- 3e2552a9c1a004336609904ae6d166ca22603d679a5f4292982515b96c708ee7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.