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
File size: 1,081 Bytes
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license: creativeml-openrail-m
language:
- en
- pt
tags:
- text-to-image
- stable-diffusion-xl
- diffusers
- imageflow
base_model: stabilityai/stable-diffusion-xl-base-1.0
pipeline_tag: text-to-image
---
# 🌊 Imageflow.1.1.1
**Text-to-Image** model by [jeffvedd](https://huggingface.co/jeffvedd)
Base: `stabilityai/stable-diffusion-xl-base-1.0`
Framework: 🤗 Diffusers
## 🚀 Uso Rápido
```python
from diffusers import StableDiffusionXLPipeline
import torch
pipe = StableDiffusionXLPipeline.from_pretrained(
'jeffvedd/Imageflow',
torch_dtype=torch.float16,
use_safetensors=True,
).to('cuda')
image = pipe(
prompt='A futuristic city at night, neon lights, ultra detailed',
negative_prompt='blurry, low quality',
num_inference_steps=30,
guidance_scale=7.5,
).images[0]
image.save('output.png')
```
## ⚙️ Parâmetros Recomendados
| Parâmetro | Valor |
|-----------|-------|
| `guidance_scale` | 7.0 – 9.0 |
| `num_inference_steps` | 25 – 40 |
| `resolution` | 1024×1024 |
**Autor:** jeffvedd · **Treinado em:** Kaggle GPU
|