open-diffusion-v1 / README.md
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---
license: creativeml-openrail-m
tags:
- text-to-image
- open-diffusion
- od-v1
- openskyml
language:
- en
- fr
- ru
pipeline_tag: text-to-image
---
# Open Diffusion V1
Generate cool images with OpenDiffusion V1 (OD-v1)
## Model Details
### Model Description
- **Developed by:** [OpenSkyML](https://huggingface.co/openskyml)
- **Model type:** [Multimodal (Text-to-Image)](https://huggingface.co/models?pipeline_tag=text-to-image)
- **License:** [CreativeML-Openrail-m](https://huggingface.co/models?license=license%3Acreativeml-openrail-m)
### Model Sources
- **Repository:** [click](https://huggingface.co/openskyml/open-diffusion-v1/tree/main)
- **Demo:**
- [demo with Gradio](https://huggingface.co/spaces/openskyml/open-diffusion)
- [demo with Docker](https://huggingface.co/spaces/openskyml/open-diffusion-docker)
## Uses
### In Free Inference API:
```py
import requests
HF_READ_TOKEN = "..."
API_URL = "https://api-inference.huggingface.co/models/openskyml/open-diffusion-v1"
headers = {"Authorization": f"Bearer {HF_READ_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))
```
### In Spaces:
```py
import gradio as gr
gr.load("models/openskyml/open-diffusion-v1").launch()
```