|
--- |
|
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](https://huggingface.co/dreambooth-hackathon) 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! |
|
|
|
<blockquote class="twitter-tweet"><p lang="sv" dir="ltr">Hasbulla Van Gogh <a href="https://t.co/5f0uPKhi6U">pic.twitter.com/5f0uPKhi6U</a></p>— Hasbulla 🐐 (@HasbullaHive) <a href="https://twitter.com/HasbullaHive/status/1610729157268234240?ref_src=twsrc%5Etfw">January 4, 2023</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> |
|
|
|
## Images generated by model |
|
|
|
<img src=https://i.imgur.com/Sqfr7ae.jpg width=70% height=70%> |
|
|
|
# Gradio & Colab |
|
|
|
Model supported in a [Gradio](https://github.com/gradio-app/gradio) Web UI and Colab: |
|
[](https://huggingface.co/spaces/carlosabadia/hasbulla) |
|
[](https://colab.research.google.com/drive/1ZB1_Z89BnjW_P76OLoQdcqVgPZfN8HEG?usp=sharing) |
|
|
|
## Usage |
|
|
|
```python |
|
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") |
|
``` |
|
|
|
 |
