This plugin integrates CompVis' Stable Diffusion 1.x text-to-image models into the dashAI platform using the Hugging Face diffusers backend. It enables flexible image generation from text prompts, with configurable inference and sampling parameters.
Original 1.x checkpoint from CompVis, based on CompVis/stable-diffusion-v1-1.
Continued training over v1-1, based on CompVis/stable-diffusion-v1-2.
Continued training with classifier-free guidance, based on CompVis/stable-diffusion-v1-3.
Most refined 1.x checkpoint, based on CompVis/stable-diffusion-v1-4.
All models are latent text-to-image diffusion models, designed for high-quality image generation and compatible with CPU or GPU inference through diffusers.
Stable Diffusion is a latent text-to-image diffusion model developed by CompVis, Stability AI, and Runway. It generates photo-realistic images from natural language descriptions.
Key features of Stable Diffusion 1.x models:
- Latent diffusion: generation runs in a compressed latent space for efficiency
- Text-conditioned: images are guided by natural language prompts
- Negative prompting: steer the model away from unwanted elements
- Open weights: freely available checkpoints
- Configurable resolution: supports a range of output dimensions
Stable Diffusion is designed for deployment on laptops, desktops, and cloud infrastructure, making advanced image generation more accessible.
- Image generation from text prompts
- Multiple 1.x checkpoints selectable at runtime
- Reproducible generation via fixed random seeds
- Configurable generation parameters:
negative_prompt: elements to avoid in the imagenum_inference_steps: number of denoising stepsguidance_scale: how strongly the model follows the promptwidth/height: output image dimensionsnum_images_per_prompt: number of images per promptdevice: detected GPU (e.g."GPU 0: NVIDIA RTX 3090 - Compute Capability 8.6") or"CPU"
| Parameter | Description | Default |
|---|---|---|
model_name |
Stable Diffusion 1.x checkpoint from Hugging Face | "CompVis/stable-diffusion-v1-1" |
negative_prompt |
Text prompt for elements to avoid in the image | "" (optional) |
num_inference_steps |
Number of denoising steps (higher = better quality, slower) | 15 |
guidance_scale |
How strongly the model follows the prompt | 3.5 |
seed |
Random seed for reproducibility (negative = random) | -1 |
width |
Width of the generated image (multiple of 8) | 512 |
height |
Height of the generated image (multiple of 8) | 512 |
num_images_per_prompt |
Number of images to generate per prompt | 1 |
device |
Inference device — a detected GPU by name (e.g. "GPU 0: NVIDIA RTX 3090 - Compute Capability 8.6") or "CPU" |
First detected GPU if available, else "CPU" |
diffuserstorch- Model files from Hugging Face:
This plugin uses the Hugging Face diffusers pipeline for text-to-image generation.
The models are pretrained for inference and are not designed for fine-tuning through this plugin. Image dimensions must be multiples of 8.