stable-diffusion-x4-upscaler

Stable Diffusion x4 upscaler - is a diffusion model for 4x image resolution upscaling based on text prompts. It takes as input a low-resolution image and a text prompt, along with the noise_level parameter.

Model type: Diffusion-based text-to-image generation model
Text encoder: Pre-trained OpenCLIP-ViT/H model.
Training: 1.25 million steps on 32 NVIDIA A100 GPUs, using the AdamW optimizer with a learning rate of 0.0001.
Input dimensions: 512x512 images and English-language text prompts.

Limitations:

• Does not provide photorealism.
• Does not generate readable text.
• Performs poorly with complex compositions in images (e.g., "a red cube on a blue sphere").

License: CreativeML Open RAIL++-M. Use is prohibited for creating harmful content (e.g., violence, sexual violence, or the spread of stereotypes).

Announce Date: 23.11.2022
Parameters: 0B
Context: 77
VRAM requirements: 0.0 GB using 4 bits quantization
Developer: Stability AI
License: OpenRail++

Use our pre-built public endpoints to test inference and explore stable-diffusion-x4-upscaler capabilities.

Rent your own physically dedicated instance with hourly or long-term monthly billing.

We recommend deploying private instances in the following scenarios:

• maximize endpoint performance,
• enable full context for long sequences,
• ensure top-tier security for data processing in an isolated, dedicated environment,
• use custom weights, such as fine-tuned models or LoRA adapters.

Contact our dedicated neural networks support team at nn@immers.cloud or send your request to the sales department at sale@immers.cloud.