Yiwu

🚀 Novelai-Diffusion

Novelai-Diffusion is a latent diffusion model capable of generating high-quality anime images. This diffusers version of the model aims to make it more accessible for everyone.

🚀 Quick Start

Novelai-Diffusion is a latent diffusion model which can create best quality anime image. Here is the diffusers version of the model, designed to simplify the use of Novelai-Diffusion for all users.

📚 Documentation

Gradio & Colab Demo

There is a Gradio Web UI and Colab with Diffusers to run Novelai Diffusion:

Run Novelai Diffusion on TPU !!! (Beta):

💻 Usage Examples

Basic Usage

pytorch

from diffusers import DiffusionPipeline
import torch

pipe = DiffusionPipeline.from_pretrained("animelover/novelai-diffusion", custom_pipeline="waifu-research-department/long-prompt-weighting-pipeline", torch_dtype=torch.float16)
pipe.safety_checker = None # we don't need safety checker. you can add not safe words to negative prompt instead.
pipe = pipe.to("cuda")

prompt = "best quality, masterpiece, 1girl, cute, looking at viewer, smiling, open mouth, white hair, red eyes, white kimono, sakura petal"
neg_prompt = "lowres, bad anatomy, error body, error hair, error arm, error hands, bad hands, error fingers, bad  fingers, missing fingers, error legs, bad legs, multiple legs, missing legs, error lighting, error shadow, error reflection, text, error, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry"
# we don't need autocast here, because autocast will make speed slow down.
image = pipe.text2img(prompt,negative_prompt=neg_prompt, width=512,height=768,max_embeddings_multiples=5,guidance_scale=12).images[0]
image.save("test.png")

onnxruntime

from diffusers import DiffusionPipeline

pipe = DiffusionPipeline.from_pretrained("animelover/novelai-diffusion", revision="onnx16",
                                         custom_pipeline="waifu-research-department/onnx-long-prompt-weighting-pipeline",
                                         provider="CUDAExecutionProvider")
pipe.safety_checker = None # we don't need safety checker. you can add not safe words to negative prompt instead.

prompt = "best quality, masterpiece, 1girl, cute, looking at viewer, smiling, open mouth, white hair, red eyes, white kimono, sakura petal"
neg_prompt = "lowres, bad anatomy, error body, error hair, error arm, error hands, bad hands, error fingers, bad  fingers, missing fingers, error legs, bad legs, multiple legs, missing legs, error lighting, error shadow, error reflection, text, error, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry"
image = pipe.text2img(prompt,negative_prompt=neg_prompt, width=512,height=768,max_embeddings_multiples=5,guidance_scale=12).images[0]
image.save("test.png")

Advanced Usage

Note: we can input long prompt and adjust weighting by using "waifu-research-department/long-prompt-weighting-pipeline". It requires diffusers>=0.4.0.

📄 Acknowledgements

Thanks to novelai for this awesome model. Support them if you can.