Instructions to use 0why0/JoDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 0why0/JoDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("0why0/JoDiffusion", 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 Label VAE models
Browse files- dense-label-vae-light-ade20k-semantic-lr1e4/config.json +22 -0
- dense-label-vae-light-ade20k-semantic-lr1e4/diffusion_pytorch_model.safetensors +3 -0
- dense-label-vae-light-coco-semantic-lr1e4/config.json +21 -0
- dense-label-vae-light-coco-semantic-lr1e4/diffusion_pytorch_model.safetensors +3 -0
- dense-label-vae-light-voc-semantic-lr1e5/config.json +21 -0
- dense-label-vae-light-voc-semantic-lr1e5/diffusion_pytorch_model.safetensors +3 -0
dense-label-vae-light-ade20k-semantic-lr1e4/config.json
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{
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"_class_name": "LightweightLabelVAE",
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"_diffusers_version": "0.30.1",
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"_name_or_path": "output/dense-label-vae-light-ade20k-semantic-lr1e4/checkpoint-25000",
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"act_fn": "none",
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"block_out_channels": [
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128,
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256,
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512,
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512
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],
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"in_channels": 8,
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"intermediate_channels": 512,
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"latent_channels": 4,
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"norm_num_groups": 32,
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"num_latents": 2,
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"num_mid_blocks": 0,
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"num_upscalers": 3,
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"out_channels": 151,
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"scaling_factor": 0.2,
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"upscale_channels": 512
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}
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dense-label-vae-light-ade20k-semantic-lr1e4/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2f105f2309300254a6fbb58598a97626005e53551adf118534311e63d858b263
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size 61675836
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dense-label-vae-light-coco-semantic-lr1e4/config.json
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{
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"_class_name": "LightweightLabelVAE",
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"_diffusers_version": "0.30.1",
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"act_fn": "none",
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"block_out_channels": [
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128,
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256,
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512,
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512
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],
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"in_channels": 7,
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"intermediate_channels": 512,
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"latent_channels": 4,
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"norm_num_groups": 32,
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"num_latents": 2,
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"num_mid_blocks": 0,
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"num_upscalers": 3,
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"out_channels": 81,
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"scaling_factor": 0.2,
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"upscale_channels": 512
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}
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dense-label-vae-light-coco-semantic-lr1e4/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:90ffed41eeb16e0f2eb89c23bc7d4df935ba4a9ac48ea6beaa81f53df384e4c8
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size 60380692
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dense-label-vae-light-voc-semantic-lr1e5/config.json
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{
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"_class_name": "LightweightLabelVAE",
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"_diffusers_version": "0.30.1",
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"act_fn": "none",
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"block_out_channels": [
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128,
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256,
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512,
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512
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],
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"in_channels": 5,
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"intermediate_channels": 512,
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"latent_channels": 4,
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"norm_num_groups": 32,
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"num_latents": 2,
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"num_mid_blocks": 0,
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"num_upscalers": 3,
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"out_channels": 21,
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"scaling_factor": 0.2,
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"upscale_channels": 512
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}
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dense-label-vae-light-voc-semantic-lr1e5/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5f7bd60a677515c7afb8f6e2f4cc653905c3b97bf22bb16b32be631ae22561f0
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size 59265316
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