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A 4-bit NF4 quantisation of layerdifforg/seethroughv0.0.1_marigold for GPUs with less memory. The UNet and the text encoder are quantised with bitsandbytes (NF4, bfloat16 compute dtype). The VAE is unquantised and identical to the full model. It is used by `inference/scripts/inference_psd_quantized.py` (the default `--quant_mode nf4`), which needs `requirements-inference-bnb.txt`. Read our GitHub repository for usage and details. The See-through code is licensed under Apache-2.0. These weights are released under Apache-2.0 for our own contributions, and they also inherit the licences of the models they are derived from:

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A 4-bit NF4 quantisation of layerdifforg/seethroughv0.0.2_layerdiff3d for GPUs with less memory. The UNet and both text encoders are quantised with bitsandbytes (NF4, bfloat16 compute dtype). The VAE and the transparent VAE are unquantised and identical to the full model. It is used by `inference/scripts/inference_psd_quantized.py` (the default `--quant_mode nf4`), which needs `requirements-inference-bnb.txt`. Read our GitHub repository for usage and details. The See-through code is licensed under Apache-2.0. These weights are released under Apache-2.0 for our own contributions, and they also inherit the licences of the models they are derived from:

Category pending
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
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