---
license: bigscience-bloom-rail-1.0
language:
- en
library_name: diffusers
tags:
- stable-diffusion
- text-to-image
---
# pony-diffusion-g5 - a new generation ~~of waifus~~
pony-diffusion-g5 is a latent text-to-image diffusion model that has been conditioned on medium-to-low-quality pony images through fine-tuning.
Finetuned for MLP G5 main characters, based on [AstraliteHeart/pony-diffusion](https://huggingface.co/AstraliteHeart/pony-diffusion)
__!!IMPORTANT: USE NEGATIVE PROMPT "3d, sfm" FOR BEST RESULT__
## Dataset criteria
All training images from Derpibooru using the search criteria below
- General: "g5, safe, solo, score.gte:250, -webm, -animate || g5, suggestive, solo, score.gte:250, -webm, -animate", 856 entries wo/ gifs, 5 epochs
- Izzy moonbow: "izzy moonbow, safe, solo, score.gte:200, -webm, -animate || izzy moonbow, suggestive, solo, score.gte:200, -webm, -animate", 531 entries wo/ gifs, 3 epochs
- Sunny starscout: "sunny starscout, safe, solo, score.gte:200, -webm, -animate || sunny starscout, suggestive, solo, score.gte:200, -webm, -animate", 252 entries wo/ gifs, 3 epochs
- Pipp petals: "pipp petals, safe, solo, score.gte:200, -webm, -animate || pipp petals, suggestive, solo, score.gte:200, -webm, -animate", 218 entries wo/ gifs, 3 epochs
- Zipp storm: "zipp storm, safe, solo, score.gte:200, -webm, -animate || pipp petals, suggestive, solo, score.gte:200, -webm, -animate", 167 entries wo/ gifs, 3 epochs
- Hitch trailblzer: "hitch trailblazer, safe, solo, score.gte:200, -webm, -animate || hitch trailblazer, suggestive, solo, score.gte:200, -webm, -animate", 34 entries wo/ gifs (wat), 3 epochs
## Why the model's quality is bad?
The amount of G5 pony images within the search criteria is little, so don't really expect the quality to be as high as the original model is
~~_Also bcs im new to ai stuff i don't know how to train datasets correctly if u could help me great thx_~~
## Example code
```python
from diffusers import StableDiffusionPipeline
import torch
from diffusers import DDIMScheduler
model_path = "./gen_model_izzy"
prompt = "(((izzy moonbow))), pony, looking at you, smiling, sitting on beach, cute, portrait, intricate, digital painting, smooth, sharp, focus, depth of field"
negative= "3d sfm"
# torch.manual_seed(1145141919810)
pipe = StableDiffusionPipeline.from_pretrained(
model_path,
torch_dtype=torch.float16,
scheduler=DDIMScheduler(
beta_start=0.00085,
beta_end=0.012,
beta_schedule="scaled_linear",
clip_sample=False,
set_alpha_to_one=True,
),
# safety_checker=None
)
pipe = pipe.to("cuda")
images = pipe(prompt, width=512, height=512, num_inference_steps=50, num_images_per_prompt=5, negative_prompt=negative).images
for i, image in enumerate(images):
image.save(f"test-{i}.png")
```
## Thanks
[AstraliteHeart/pony-diffusion](https://huggingface.co/AstraliteHeart/pony-diffusion), for providing a solid start-point to train on
This project would not have been possible without the incredible work by the [CompVis Researchers](https://ommer-lab.com/).
With special thanks to [Waifu-Diffusion](https://huggingface.co/hakurei/waifu-diffusion) for providing finetuning expertise and [Novel AI](https://novelai.net/) for providing necessary compute.
---
license: bigscience-bloom-rail-1.0
---