Image Classification
Transformers
PyTorch
ONNX
Safetensors
beit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use NTQAI/pedestrian_gender_recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NTQAI/pedestrian_gender_recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="NTQAI/pedestrian_gender_recognition") 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("NTQAI/pedestrian_gender_recognition") model = AutoModelForImageClassification.from_pretrained("NTQAI/pedestrian_gender_recognition") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding ONNX file of this model
#1
by ivensamdh - opened
- model.onnx +3 -0
model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:231fec789fc9d5ab84d75e137f7f213a0c9b2f5afdb1be55ebef7d45a7a8a347
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size 365257740
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