metadata

base_model: stabilityai/stable-diffusion-2-1
instance_prompt: a hand drawn painting in the style of picasso with geometric shapes
tags:
  - text-to-image
  - diffusers
  - autotrain
inference: true

DreamBooth trained by AutoTrain

Text encoder was not trained.
This is the model that feeds the Google Colab Notebook.
The model is a simplified version of the DreamBooth model.

Here is how to use the model:

import requests

API_URL = "https://api-inference.huggingface.co/models/sourceoftruthdata/sot_autotrain_dreambooth_v1" headers = {"Authorization": "Bearer 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"}

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))