Instructions to use minchul/cvlface_adaface_ir50_ms1mv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minchul/cvlface_adaface_ir50_ms1mv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="minchul/cvlface_adaface_ir50_ms1mv2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("minchul/cvlface_adaface_ir50_ms1mv2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload directory
Browse files
pretrained_model/config.yaml
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pipelines:
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eval_pipeline_name: infer_model_pipeline
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