Image Classification
Transformers
Safetensors
vit
image-classification, faces-recognition
Generated from Trainer
Instructions to use al-css/faces_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use al-css/faces_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="al-css/faces_classification") 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("al-css/faces_classification") model = AutoModelForImageClassification.from_pretrained("al-css/faces_classification") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files- config.json +1 -1
- model.safetensors +1 -1
config.json
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{
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"_name_or_path": "
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"architectures": [
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"ViTForImageClassification"
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],
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{
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"_name_or_path": "lokeshk/Face-Recognition-NM",
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"architectures": [
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"ViTForImageClassification"
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],
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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oid sha256:174196833aa1e1b4bc5f5396600b0af40c68f95235febb9084f27b7afed0cbb4
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size 343525432
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