Instructions to use Poomz/loreitup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Poomz/loreitup with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Poomz/loreitup", 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
Upload model_index.json
Browse files- model_index.json +16 -0
model_index.json
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{
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"_class_name": "DiTPipeline",
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"_diffusers_version": "0.27.2",
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"scheduler": [
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"diffusers",
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"DDIMScheduler"
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],
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"transformer": [
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"diffusers",
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"Transformer2DModel"
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],
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"vae": [
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"diffusers",
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"AutoencoderKL"
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]
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}
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