Instructions to use TensorStack/AutoEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TensorStack/AutoEncoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TensorStack/AutoEncoder", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Upload 2 files
Browse files
LongCatAudio/config.json
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{
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"_class_name": "LongCatAudioDiTVae",
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"_diffusers_version": "0.38.0.dev0",
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"act_fn": null,
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"c_mults": [
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],
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"channels": 128,
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"downsample_shortcut": "averaging",
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"downsampling_ratio": 2048,
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"encoder_latent_dim": 128,
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"final_tanh": false,
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"in_channels": 1,
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"in_shortcut": "duplicating",
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"latent_dim": 64,
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"out_shortcut": "averaging",
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"sample_rate": 24000,
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"scale": 0.71,
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"strides": [
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],
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"upsample_shortcut": "duplicating",
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"use_snake": true
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}
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LongCatAudio/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2f46bc743439b6ffce657b5805ec5d8214204c0aaf6cf6426a8b66b8cc8356b3
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size 624466876
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