Instructions to use ericxlima/DogsClassifierModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ericxlima/DogsClassifierModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ericxlima/DogsClassifierModel") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("ericxlima/DogsClassifierModel") model = AutoModel.from_pretrained("ericxlima/DogsClassifierModel") - Notebooks
- Google Colab
- Kaggle
Create scheduler
Browse files
scheduler
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{
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"_class_name": "DDIMScheduler",
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"_diffusers_version": "0.8.0",
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"beta_end": 0.012,
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"beta_schedule": "scaled_linear",
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"beta_start": 0.00085,
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"clip_sample": false,
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"num_train_timesteps": 1000,
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"prediction_type": "v_prediction",
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"set_alpha_to_one": false,
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"skip_prk_steps": true,
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"steps_offset": 1,
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"trained_betas": null
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}
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