Text-to-Image
Diffusers
Safetensors
English
Portuguese
StableDiffusionXLPipeline
stable-diffusion-xl
imageflow
Instructions to use BinaryLight1011/Imageflow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BinaryLight1011/Imageflow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BinaryLight1011/Imageflow", 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
Add Model Card — Imageflow.1.1.1
Browse files
README.md
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# 🌊 Imageflow.1.1.1
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**Text-to-Image** model by [
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Base: `stabilityai/stable-diffusion-xl-base-1.0`
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Framework: 🤗 Diffusers
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import torch
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pipe = StableDiffusionXLPipeline.from_pretrained(
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torch_dtype=torch.float16,
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use_safetensors=True,
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).to('cuda')
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| `num_inference_steps` | 25 – 40 |
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| `resolution` | 1024×1024 |
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**Autor:**
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# 🌊 Imageflow.1.1.1
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**Text-to-Image** model by [jeffvedd](https://huggingface.co/jeffvedd)
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Base: `stabilityai/stable-diffusion-xl-base-1.0`
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Framework: 🤗 Diffusers
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import torch
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pipe = StableDiffusionXLPipeline.from_pretrained(
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'jeffvedd/Imageflow',
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torch_dtype=torch.float16,
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use_safetensors=True,
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).to('cuda')
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| `num_inference_steps` | 25 – 40 |
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| `resolution` | 1024×1024 |
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**Autor:** jeffvedd · **Treinado em:** Kaggle GPU
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