Text-to-Image
Diffusers
Safetensors
MiniMax H3
Pruna AI
English
image-to-image
image-generation
image-editing
prompt-upsampling
modular-diffusers
Instructions to use PrunaAI/P-H3-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PrunaAI/P-H3-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("PrunaAI/P-H3-Image", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Pruna AI
How to use PrunaAI/P-H3-Image with Pruna AI:
from pruna import PrunaModel pip install -U diffusers transformers accelerate
from pruna import PrunaModel import torch # switch to "mps" for apple devices pipe = PrunaModel.from_pretrained("PrunaAI/P-H3-Image", 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 Settings
- Draw Things
- DiffusionBee
Use the trained sampling grid
Browse files- modular_model_index.json +3 -3
modular_model_index.json
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"vision_pixels": 1000000,
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"sample_sigmas": [
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1.0,
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0.
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0.
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0.978136,
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0.951688,
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0.925372,
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0.810083,
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0.528718,
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0.0
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"vision_pixels": 1000000,
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"sample_sigmas": [
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1.0,
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+
0.984753,
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0.967905,
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0.951688,
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0.925372,
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0.881923,
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0.810083,
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0.528718,
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0.0
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