Model reference · open weights

mo-di-diffusion

Available as managed deployment Image nitrosocke · community Text→image 1 variants 1k dl/mo

mo-di-diffusion is an open-weight image model from nitrosocke. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Released bynitrosocke
TypeImage models
TaskText→image
Runs withdiffusers
Released2022-10-27
Popularity1k downloads / month
LicenceOpen weights

About

What mo-di-diffusion is

Mo Di Diffusion

This is the fine-tuned Stable Diffusion 1.5 model trained on screenshots from a popular animation studio. Use the tokens modern disney style in your prompts for the effect.

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Videogame Characters rendered with the model: Animal Characters rendered with the model: Cars and Landscapes rendered with the model:

Prompt and settings for Lara Croft:

modern disney lara croft Steps: 50, Sampler: Euler a, CFG scale: 7, Seed: 3940025417, Size: 512x768

Prompt and settings for the Lion:

modern disney (baby lion) Negative prompt: person human Steps: 50, Sampler: Euler a, CFG scale: 7, Seed: 1355059992, Size: 512x512

This model was trained using the diffusers based dreambooth training by ShivamShrirao using prior-preservation loss and the train-text-encoder flag in 9.000 steps.

Read the full model card

🧨 Diffusers

This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion.

You can also export the model to ONNX, MPS and/or FLAX/JAX.

from diffusers import StableDiffusionPipeline
import torch

model_id = "nitrosocke/mo-di-diffusion"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "a magical princess with golden hair, modern disney style"
image = pipe(prompt).images[0]

image.save("./magical_princess.png")

Gradio & Colab

We also support a Gradio Web UI and Colab with Diffusers to run fine-tuned Stable Diffusion models:

License

This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies:

  1. You can't use the model to deliberately produce nor share illegal or harmful outputs or content
  2. The authors claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
  3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully) Please read the full license here

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys mo-di-diffusion for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (mo-di-diffusion below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/images/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"mo-di-diffusion","prompt":"a red bicycle","size":"1024x1024"}'

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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