Text-to-Image
Sana
Diffusers
Safetensors
English
Chinese
Sana
1024px_based_image_size
Multi-language
Instructions to use Efficient-Large-Model/Sana_1600M_1024px_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Sana
How to use Efficient-Large-Model/Sana_1600M_1024px_diffusers with Sana:
# Load the model and infer image from text import torch from app.sana_pipeline import SanaPipeline from torchvision.utils import save_image sana = SanaPipeline("configs/sana_config/1024ms/Sana_1600M_img1024.yaml") sana.from_pretrained("hf://Efficient-Large-Model/Sana_1600M_1024px_diffusers") image = sana( prompt='a cyberpunk cat with a neon sign that says "Sana"', height=1024, width=1024, guidance_scale=5.0, pag_guidance_scale=2.0, num_inference_steps=18, ) - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -102,7 +102,7 @@ import torch
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from diffusers import SanaPAGPipeline
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pipe = SanaPAGPipeline.from_pretrained(
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"Efficient-Large-Model/
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variant="fp16",
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torch_dtype=torch.float16,
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pag_applied_layers="transformer_blocks.8",
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from diffusers import SanaPAGPipeline
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pipe = SanaPAGPipeline.from_pretrained(
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"Efficient-Large-Model/Sana_1600M_1024px_diffusers",
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variant="fp16",
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torch_dtype=torch.float16,
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pag_applied_layers="transformer_blocks.8",
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