Use the activation token timeless style in your prompt (I recommend at the start)
Trained from 1.5 with VAE. - This is a dreambooth model trained on a diverse set of colourized photographs from the 1880s-1980s.
The goal of this model was to create striking images with rich tones and an anachronistic feel.
When using this model, I typically use painted illustration blur haze monochrome in my negative prompt. I encourage you to experiment and see what works well for you.
Please see this document where I share the parameters (prompt, sampler, seed, etc.) used for all example images.
I look forward to seeing everyone's cool creations!
Timeless Diffusion is a highly specialized Image generation AI Model of type Safetensors / Checkpoint AI Model created by AI community user wavymulder. Derived from the powerful Stable Diffusion (SD 1.5) model, Timeless Diffusion has undergone an extensive fine-tuning process, leveraging the power of a dataset consisting of images generated by other AI models or user-contributed data. This fine-tuning process ensures that Timeless Diffusion is capable of generating images that are highly relevant to the specific use-cases it was designed for, such as photography, vivid colors.
With a rating of 5 and over 2 ratings, Timeless Diffusion is a popular choice among users for generating high-quality images from text prompts.
Yes! You can download the latest version of Timeless Diffusion from here.
To use Timeless Diffusion, download the model checkpoint file and set up an UI for running Stable Diffusion models (for example, AUTOMATIC1111). Then, provide the model with a detailed text prompt to generate an image. Experiment with different prompts and settings to achieve the desired results. If this sounds a bit complicated, check out our initial guide to Stable Diffusion – it might be of help. And if you really want to dive deep into AI image generation and understand how set up AUTOMATIC1111 to use Safetensors / Checkpoint AI Models like Timeless Diffusion, check out our crash course in AI image generation.