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Realistic Vision V6.0 B1 noVAE - AI Image Models Tool

Overview

Realistic Vision V6.0 B1 noVAE is a beta text-to-image diffusion model released on Hugging Face that emphasizes photorealism and fine detail. The model is presented as part of the Realistic Vision V6.0 “New Vision” family and is intended for users who want realistic imagery (portraits, product shots, environmental photography) while retaining control over the VAE choice and generation pipeline. The model card on Hugging Face provides explicit guidance on resolution choices, generation parameters, and recommended workflows, and the noVAE variant intentionally omits a VAE so users can attach a compatible VAE that best suits their downstream quality goals. Designed for integration with common text-to-image pipelines, Realistic Vision V6.0 B1 noVAE is distributed under the creativeml-openrail-m license and has been actively used by the community (see the model page for example galleries and usage notes). The Hugging Face page also contains practical recommendations and example prompts; users typically pair this model with a high-quality VAE and standard schedulers from the Diffusers ecosystem to maximize photorealistic output quality. For the latest details, examples, and usage tips, consult the official model page on Hugging Face.

Model Statistics

Downloads: 26,126
Likes: 289
Pipeline: text-to-image

License: creativeml-openrail-m

Model Details

Realistic Vision V6.0 B1 noVAE is a diffusion-based text-to-image model intended for photorealistic generation. The model card describes it as a beta release in the Realistic Vision V6.0 family and emphasizes production-oriented workflows, including recommended resolutions and generation settings. The repository variant labeled "noVAE" does not include a VAE component, so users should supply a compatible VAE (for example, an sd-vae or other community VAE) when instantiating a Diffusers pipeline. The package is intended to be used with standard text-to-image pipelines (Diffusers/Stable Diffusion pipelines). The model card provides guidance on generation parameters and resolution tradeoffs but does not publish exact architecture parameter counts in the model repository. The model is distributed under the creativeml-openrail-m license. For source files, example prompts, galleries, and the author’s recommended workflows, see the model page on Hugging Face.

Key Features

Beta-focused photorealistic text-to-image model emphasizing realism and fine detail
noVAE variant omits VAE so users can choose a compatible VAE for tailored quality
Model card includes detailed generation guidance, resolution tips, and workflows
Designed for use with Diffusers/Stable Diffusion pipelines and standard schedulers
Distributed under the creativeml-openrail-m license with example galleries on Hugging Face

Example Usage

Example (python):

from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
import torch

# Repo for the model on Hugging Face
repo_id = "SG161222/Realistic_Vision_V6.0_B1_noVAE"
# If the noVAE release omits a VAE, provide a compatible VAE checkpoint (example shown)
vae_repo = "stabilityai/sd-vae-ft-mse"

# Load the pipeline, supplying an external VAE if required
pipe = StableDiffusionPipeline.from_pretrained(
    repo_id,
    vae=vae_repo,
    torch_dtype=torch.float16,
    safety_checker=None,  # optional: follow your safety policy
)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")

prompt = "A photorealistic portrait of a woman at golden hour, detailed skin texture, shallow depth of field"

image = pipe(prompt, guidance_scale=7.5, num_inference_steps=25, height=768, width=512).images[0]
image.save("realistic_vision_v6_output.png")

# Notes:
# - The noVAE variant intentionally excludes a VAE; pass a VAE repo (like the example) when loading.
# - Adjust guidance_scale, steps, and resolution per the model card recommendations on Hugging Face.