Instructions to use rupeshs/taesdxl-openvino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rupeshs/taesdxl-openvino with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rupeshs/taesdxl-openvino", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload config.json
Browse files- config.json +46 -38
config.json
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"_class_name": "AutoencoderTiny",
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"_diffusers_version": "0.
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"_name_or_path": "madebyollin/taesdxl",
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"act_fn": "relu",
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"_class_name": "AutoencoderTiny",
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"_diffusers_version": "0.33.0",
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"_name_or_path": "madebyollin/taesdxl",
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"act_fn": "relu",
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"block_out_channels": [
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"decoder_block_out_channels": [
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"encoder_block_out_channels": [
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"force_upcast": false,
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"in_channels": 3,
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"latent_channels": 4,
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"latent_magnitude": 3,
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"latent_shift": 0.5,
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"num_decoder_blocks": [
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"out_channels": 3,
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"scaling_factor": 1.0,
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"shift_factor": 0.0,
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"upsample_fn": "nearest",
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"upsampling_scaling_factor": 2
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}
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