Average Model Cost: $0.0033
Number of Runs: 46,610
Models by this creator
The RunDiffusion FX Photorealistic model is a text-to-image model developed by RunDiffusion. It is capable of generating photorealistic images from textual descriptions. This model uses advanced algorithms and deep learning techniques to accurately depict the details in the provided text and produce high-quality, realistic images.
The SDXL Canny controlnet with LoRa support model is a text-to-image AI model. It generates images based on the provided text prompts. The model takes various parameters like seed, image, prompt, refine, scheduler, lora_scale, num_outputs, lora_weights, refine_steps, guidance_scale, apply_watermark, condition_scale, negative_prompt, num_inference_steps and returns an image URL in response. For instance, when given a prompt such as "a woman in Alaska in the style of sksfer", it will output an image based on this information. It also allows the manipulation of various features of the image through the input parameters, such as refining the base image, applying a watermark and varying the guidance scale.
The photorealistic-fx-lora model is a text-to-image model that generates realistic images based on textual descriptions. It incorporates the LoRA (Latent Optimization with Reinforcement Learning and Attention) algorithm to enhance image quality. The model has been shown to perform on par with, or even better than, the RealisticVision model.
The photorealistic-fx-controlnet model is an implementation of ControlNet for the RunDiffusion PhotorealisticFX model. This model is designed to generate photorealistic images from a given input. ControlNet is used to guide the generation process and allows for controlling specific attributes of the output image, such as the colors or lighting. This model is aimed at technical users who want to have fine-grained control over the generated images.