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README.md
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license: creativeml-openrail-m
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tags:
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- text-to-image
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---
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### Open-Diffusion-V3 Dreambooth model trained by ehristoforu with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
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license: creativeml-openrail-m
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tags:
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- text-to-image
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- open-diffusion
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- od-v3
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- openskyml
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language:
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- en
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- fr
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- ru
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pipeline_tag: text-to-image
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---
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# Open Diffusion V3
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Generate cool images with OpenDiffusion V3 (OD-v3)
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## Model Details
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### Model Description
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- **Developed by:** [OpenSkyML](https://huggingface.co/openskyml)
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- **Model type:** [Multimodal (Text-to-Image)](https://huggingface.co/models?pipeline_tag=text-to-image)
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- **License:** [CreativeML-Openrail-m](https://huggingface.co/models?license=license%3Acreativeml-openrail-m)
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### Model Sources
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- **Repository:** [click](https://huggingface.co/openskyml/open-diffusion-v3/tree/main)
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- **Demo [optional]:** In developed ...
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## Uses
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### In Free Inference API:
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```py
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import requests
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HF_READ_TOKEN = "..."
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API_URL = "https://api-inference.huggingface.co/models/openskyml/open-diffusion-v3"
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headers = {"Authorization": f"Bearer {HF_READ_TOKEN}"}
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def query(payload):
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response = requests.post(API_URL, headers=headers, json=payload)
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return response.content
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image_bytes = query({
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"inputs": "Astronaut riding a horse",
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})
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# You can access the image with PIL.Image for example
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import io
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from PIL import Image
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image = Image.open(io.BytesIO(image_bytes))
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```
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### In Spaces:
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```py
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import gradio as gr
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gr.load("models/openskyml/open-diffusion-v3").launch()
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```
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