Instructions to use ishan24/Sana_1600M_1024px_BF16_ControlNet_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ishan24/Sana_1600M_1024px_BF16_ControlNet_diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ishan24/Sana_1600M_1024px_BF16_ControlNet_diffusers", 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
- Local Apps
- Draw Things
- DiffusionBee
Update config.json
Browse files- config.json +1 -1
config.json
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"norm_eps": 1e-06,
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"num_attention_heads": 70,
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"num_cross_attention_heads": 20,
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"
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"out_channels": 32,
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"patch_size": 1,
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"sample_size": 32
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"norm_eps": 1e-06,
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"num_attention_heads": 70,
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"num_cross_attention_heads": 20,
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"num_layers": 7,
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"out_channels": 32,
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"patch_size": 1,
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"sample_size": 32
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