Acertainthing

🚀 ACertainThing

ACertainThing is a text - to - image model based on Stable Diffusion. It offers an alternative for generating high - quality images, especially suitable for those who are not proficient in writing prompts.

🚀 Quick Start

Try full functions with Google Colab free T4

✨ Features

Anything3.0 is an overfitted model. It takes liberties when generating human images and certain details. The community rates it highly because even users with poorly - written prompts can generate high - quality images using this overfitted model.

This ACertain version of Anything3.0 is made with Dreambooth (integrating the idea of LoRA) and initialized with ACertainModel.

However, this model has two major problems:

• It doesn't always adhere to the prompts, adding irrelevant and sometimes highly homogenized details.
• It is an unstable, overfitted model, not suitable for further training.

Despite these issues, it can make poorly - written prompts produce good output images, allowing users who are not good at writing prompts to quickly surpass those who study prompt - writing carefully.

📦 Installation

This section is not provided in the original README, so it is skipped.

💻 Usage Examples

Basic Usage

If you want to use this model for image generation, you can refer to the following code:

from diffusers import StableDiffusionPipeline
import torch

model_id = "JosephusCheung/ACertainThing"
branch_name= "main"

pipe = StableDiffusionPipeline.from_pretrained(model_id, revision=branch_name, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "pikachu"
image = pipe(prompt).images[0]

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

Advanced Usage

When using the Hosted inference API for online preview or generation with this model:

• Parameters are not allowed to be modified. It seems to be generated with Clip skip: 1. For better performance, it is strongly recommended to use Clip skip: 2.
• Here is an example of inference settings, if applicable on your own server: Steps: 28, Sampler: Euler a, CFG scale: 11, Clip skip: 2.

📚 Documentation

Examples

Below are some examples of images generated using this model, which perform better on framing, hand gestures, and moving objects compared to other analogues:

Anime Girl:

1girl, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, falling leaves, garden
Steps: 28, Sampler: Euler a, CFG scale: 11, Seed: 114514, Clip skip: 2

Anime Boy:

1boy, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, falling leaves, garden
Steps: 28, Sampler: Euler a, CFG scale: 11, Seed: 114514, Clip skip: 2

About the Model

If you want your prompts to be accurately output and want to learn the correct skills for using prompts, it is recommended that you use the more balanced model ACertainModel.

Is it a NovelAI based model? What is the relationship with SD1.2 and SD1.4?

See ASimilarityCalculatior

🔧 Technical Details

This section is not provided in the original README, so it is skipped.

📄 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 claim 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

⚠️ Important Note

The author personally opposes all forms of model merging as it has no scientific principle and is a waste of time. But the author respects the choices and preferences of the community.

💡 Usage Tip

For more accurate prompt output and to learn correct prompt - using skills, use the more balanced model ACertainModel.