Text-to-3D
Diffusers
Safetensors
English
StableDiffusionUpscaleLDM3DPipeline
stable-diffusion
stable-diffusion-diffusers
text-to-image
Eval Results (legacy)
Instructions to use Intel/ldm3d-sr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Intel/ldm3d-sr with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Intel/ldm3d-sr", 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
Update unet/config.json
Browse files- unet/config.json +4 -4
unet/config.json
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"_name_or_path": "hf-models/stable-diffusion-x4-upscaler/unet",
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"act_fn": "silu",
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"attention_head_dim": 8,
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"block_out_channels": [
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320,
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],
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"center_input_sample": false,
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"cross_attention_dim": 1024,
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"_name_or_path": "hf-models/stable-diffusion-x4-upscaler/unet",
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"act_fn": "silu",
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"attention_head_dim": 8,
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"block_out_channels": [
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320,
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640,
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1280,
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1280
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],
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"center_input_sample": false,
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"cross_attention_dim": 1024,
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