File size: 1,351 Bytes
8b10f29 1521df7 0cf65a4 a107fb8 8b10f29 a107fb8 8b10f29 a107fb8 8b10f29 a107fb8 8b10f29 a107fb8 894e64e a107fb8 d0bc54a a107fb8 |
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 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
license: creativeml-openrail-m
tags:
- text-to-image
- safetensors
- onnx
- open-diffusion
- od-v2
- openskyml
language:
- en
- fr
- ru
pipeline_tag: text-to-image
---
# Open Diffusion V2
Generate cool images with OpenDiffusion V2 (OD-v2)
## 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/ehristoforu/open-diffusion-v2/tree/main)
- **Demo [optional]:** In developed ...
## Uses
### In Free Inference API:
```py
import requests
HF_READ_TOKEN = "..."
API_URL = "https://api-inference.huggingface.co/models/openskyml/open-diffusion-v2"
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-v2").launch()
```
|