Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Art
Fantasy
General purpose
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/SQUEE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/SQUEE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/SQUEE", 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
Commit History
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Adding `diffusers` weights of this model
This PR adds fp32 and fp16 weights in PyTorch and safetensors format to Yntec/SQUEEc5455b9 -
Rename SQUEE.safetensors to SQUEEE.safetensors
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Delete model_index.json
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Rename SQUEE.safetensors to SQUEE_ema.safetensors
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Update model_index.json
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Update scheduler/scheduler_config.json
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Create README.md
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Cleanup
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Delete model_index.json
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Adding `diffusers` weights of this model (#1)
- Adding `diffusers` weights of this model (ddc26061e44d075cd7c1b5ecf4f642d794330dc6)664c101 -
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initial commit
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