Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
art
image-generation
abstract-art
stable-diffusion
Instructions to use cz9dev/herminia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cz9dev/herminia with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cz9dev/herminia", 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: 1,158 Bytes
c1812b7 6e4e124 c1812b7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | ---
tags:
- art
- image-generation
- abstract-art
- stable-diffusion
license: mit
library_name: diffusers
pipeline_tag: text-to-image
base_model: stabilityai/stable-diffusion-v1-5
---
# Herminia, modelo de generación de imágenes
Modelo herminia creado a partir de Stable Diffusion para generar imágenes a partir de texto.
## Uso con GPU
```python
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained("cz9dev/herminia", torch_dtype=torch.float16)
pipe.to("cuda")
image = pipe("Un astronauta montando un unicornio").images[0]
image.save("astronauta.png")
```
## Uso con CPU
```python
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained("cz9dev/herminia", torch_dtype=torch.float32)
pipe.to("cpu")
image = pipe("Arte fantástico con criaturas mitológicas").images[0]
image.save("astronauta.png")
```
## Ejemplos de imágenes generadas
 "Paisaje futurista de la tierra"
 "Un dibujo abstracto de la bandera cubana"
## Licencia
MIT |