Text-to-Image
Diffusers
Safetensors
English
French
Russian
StableDiffusionPipeline
open-diffusion
od-v3
openskyml
Instructions to use openskyml/open-diffusion-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use openskyml/open-diffusion-v3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("openskyml/open-diffusion-v3", 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: 1,340 Bytes
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license: creativeml-openrail-m
tags:
- text-to-image
- open-diffusion
- od-v3
- openskyml
language:
- en
- fr
- ru
pipeline_tag: text-to-image
pinned: true
---
# Open Diffusion V3
Generate cool images with OpenDiffusion V3 (OD-v3)
## 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-v3/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-v3"
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-v3").launch()
```
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