Hugging Face's logo

carlosabadia
/
hasbulla

Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
wildcard
Inference Endpoints
Model card Files Community
2
hasbulla / README.md
carlosabadia's picture
carlosabadia
Update README.md
bcd04b6
preview code
|
raw
history blame
2.55 kB
metadata
license: creativeml-openrail-m
tags:
  - pytorch
  - diffusers
  - stable-diffusion
  - text-to-image
  - diffusion-models-class
  - dreambooth-hackathon
  - wildcard
widget:
  - text: a photo of hasbulla person

DreamBooth model for the hasbulla concept trained by carlosabadia on the carlosabadia/hasbulla dataset. DreamBooth Hackaton's Winner! 🏆

This is a Stable Diffusion model fine-tuned on the hasbulla concept with DreamBooth. It can be used by modifying the instance_prompt: hasbulla person

This model was created as part of the DreamBooth Hackathon 🔥. Visit the organisation page for instructions on how to take part!

Description

This is a Stable Diffusion model fine-tuned on Hasbulla images for the wildcard theme.

It was also featured in Hasbulla's Twitter account!

Images generated by model

Gradio & Colab

Model supported in a Gradio Web UI and Colab: Open In Spaces Open In Colab

Usage 

import torch
from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler

pipe = StableDiffusionPipeline.from_pretrained(
    "carlosabadia/hasbulla", 
    scheduler = DPMSolverMultistepScheduler.from_pretrained("carlosabadia/hasbulla", subfolder="scheduler"),
    torch_dtype=torch.float16,
).to("cuda")

guidance_scale = 7
prompt = "A portrait of hasbulla person"

images = pipe(prompt, num_images_per_prompt=1, num_inference_steps=25, guidance_scale=guidance_scale).images
image = images[0]
image.save("hasbulla.png")

visitors