dreamshaper 7

ProviderLykon
Categorytext-to-image
Licensecreativeml-openrail-m
Downloads904.5K
Stars0

Overview

DreamShaper 7 is a refined Stable Diffusion checkpoint designed to bridge the gap between photorealism and digital art. For developers building generative pipelines, it offers a more versatile aesthetic than base SD models, reducing the need for complex prompt engineering to achieve high-quality lighting and anatomical accuracy. It excels in portraiture, concept art, and architectural visualization, making it a reliable choice for integrating AI-generated assets into games or UI prototypes. Because it maintains compatibility with the standard Stable Diffusion ecosystem, it integrates seamlessly with existing LoRA weights and ControlNet modules, allowing for precise structural control without sacrificing visual fidelity.

Highlights

  • Balanced blend of photorealism and stylized digital art
  • Reduced prompt engineering for high-quality visual outputs
  • Full compatibility with Stable Diffusion LoRAs and ControlNet
  • Optimized for portraits, concept art, and environment design

Usage

Install
# Install Hugging Face transformers
pip install transformers torch
SDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("Lykon/dreamshaper-7")
tokenizer = AutoTokenizer.from_pretrained("Lykon/dreamshaper-7")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance:Before downloading, install huggingface_hub with:

Guidance
pip install -U huggingface_hub

CLI Download

Download the full repository

Download the full repository
huggingface-cli download Lykon/dreamshaper-7

Download a single file to a local folder (e.g. config.json into ./dir)

Download a single file to a local folder (e.g. config.json into ./dir)
huggingface-cli download Lykon/dreamshaper-7 config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

SDK Download
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('Lykon/dreamshaper-7')

Git Download

Make sure git-lfs is installed first

Git Download
git lfs install
git clone https://huggingface.co/Lykon/dreamshaper-7

To skip LFS large-file downloads, use:

Skip LFS
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Lykon/dreamshaper-7

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

Install Transformers
pip install -U transformers torch

Load the model and run inference

Load the model and run inference
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('Lykon/dreamshaper-7')
tokenizer = AutoTokenizer.from_pretrained('Lykon/dreamshaper-7')

Full Documentation

来源: HuggingFace

---
language:

  • en

license: creativeml-openrail-m
tags:
  • stable-diffusion

  • stable-diffusion-diffusers

  • text-to-image

  • art

  • artistic

  • diffusers

  • anime

  • dreamshaper

duplicated_from: lykon/dreamshaper-7
---

Dreamshaper 7

lykon/dreamshaper-7 is a Stable Diffusion model that has been fine-tuned on runwayml/stable-diffusion-v1-5.

Please consider supporting me:


Diffusers

For more general information on how to run text-to-image models with 🧨 Diffusers, see the docs.

1. Installation

code
pip install diffusers transformers accelerate

2. Run

py
from diffusers import AutoPipelineForText2Image, DEISMultistepScheduler
import torch

pipe = AutoPipelineForText2Image.from_pretrained('lykon/dreamshaper-7', torch_dtype=torch.float16, variant="fp16")
pipe.scheduler = DEISMultistepScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")

prompt = "portrait photo of muscular bearded guy in a worn mech suit, light bokeh, intricate, steel metal, elegant, sharp focus, soft lighting, vibrant colors"

generator = torch.manual_seed(33)
image = pipe(prompt, generator=generator, num_inference_steps=25).images[0]
image.save("./image.png")

![](./image.png)

Notes

  • Version 8 focuses on improving what V7 started. Might be harder to do photorealism compared to realism focused models, as it might be hard to do anime compared to anime focused models, but it can do both pretty well if you're skilled enough. Check the examples!
  • Version 7 improves lora support, NSFW and realism. If you're interested in "absolute" realism, try AbsoluteReality.
  • Version 6 adds more lora support and more style in general. It should also be better at generating directly at 1024 height (but be careful with it). 6.x are all improvements.
  • Version 5 is the best at photorealism and has noise offset.
  • Version 4 is much better with anime (can do them with no LoRA) and booru tags. It might be harder to control if you're used to caption style, so you might still want to use version 3.31. V4 is also better with eyes at lower resolutions. Overall is like a "fix" of V3 and shouldn't be too much different.
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