license: openrail | |
language: | |
- en | |
- ru | |
library_name: diffusers | |
pipeline_tag: text-to-image | |
tags: | |
- midjourney | |
- midjourney V6 | |
- v6 | |
- MJ | |
- mj | |
- kviai | |
- kvikontent | |
- text-to-image | |
- lora | |
base_model: runwayml/stable-diffusion-v1-5 | |
widget: | |
- text: ed sheeran made of thnderstorm clouds, lights, thunder, rain, particles | |
output: | |
url: images/ed.png | |
- text: silhouette of a dog in the thunderstorm clouds, thumder, photo, bad weather, | |
output: | |
url: images/dog.png | |
- text: >- | |
A professional photo of a beautiful night waterfall in the jungle with a | |
touch of blue and a few fireflies flying around | |
output: | |
url: images/water.png | |
# Midjourney V6 | |
Midjourney is most realistic and powerful ai image generator in the world. Here is is Stable Diffusion LoRA model trained on 100k+ midjourney V6 images. | |
## Examples | |
<Gallery /> | |
## Usage | |
You can use this model using huggingface Interface API: | |
```Python | |
import requests | |
API_URL = "https://api-inference.huggingface.co/models/Kvikontent/midjourney-v6" | |
headers = {"Authorization": "Bearer HUGGINGFACE_API_TOKEN"} | |
def query(payload): | |
response = requests.post(API_URL, headers=headers, json=payload) | |
return response.content | |
image_bytes = query({ | |
"inputs": "Astronaut riding a horse", | |
}) | |
# You can access the image with PIL.Image for example | |
import io | |
from PIL import Image | |
image = Image.open(io.BytesIO(image_bytes)) | |
``` |