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flymy-ai/qwen-image-realism-lora
qwen-image-realism-lora is a text-to-image model from flymy-ai. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as apache-2.0.
Downloads · 30 days
3.8K
6% of all-time downloads
All-time downloads
62.8K
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.safetensors94.4 MB · 88%
From the Hugging Face model README
Lora for Qwen-Image
Realism word required
from diffusers import DiffusionPipeline
import torch
model_name = "Qwen/Qwen-Image"
# Load the pipeline
if torch.cuda.is_available():
torch_dtype = torch.bfloat16
device = "cuda"
else:
torch_dtype = torch.float32
device = "cpu"
pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
pipe = pipe.to(device)
# Load LoRA weights
pipe.load_lora_weights('flymy_realism.safetensors', adapter_name="lora")
prompt = '''Super Realism portrait of a teenager woman of African descent, serene calmness, arms crossed, illuminated by dramatic studio lighting, sunlit park in the background, adorned with delicate jewelry, three-quarter view, sun-kissed skin with natural imperfections, loose shoulder-length curls, slightly squinting eyes, environmental street portrait with text "FLYMY AI" on t-shirt.'''
negative_prompt = " "
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
width=1024,
height=1024,
num_inference_steps=50,
true_cfg_scale=5,
generator=torch.Generator(device="cuda").manual_seed(346346)
)
# Display the image (in Jupyter or save to file)
image.show()
# or
image.save("output.png")

We provide a ready-to-use ComfyUI workflow that works with our trained LoRA models. Follow these steps to set up and use the workflow:
Download the latest ComfyUI:
Install ComfyUI:
Download Qwen-Image model weights:
Place Qwen-Image weights in ComfyUI:
ComfyUI/models/Download our pre-trained LoRA weights:
.safetensors filesPlace LoRA weights in ComfyUI:
flymy-ai/qwen-image-lora/pytorch_lora_weights.safetensors to ComfyUI/models/loras/Load the workflow:
qwen_image_lora_example.json located in this repositoryThe ComfyUI workflow provides a user-friendly interface for generating images with our trained LoRA models without needing to write Python code.

Below are comparison images showing the improvements of our LoRA model across different scenarios:
Prompt: "realism, mountain landscape at golden hour, low sun grazing alpine meadows, crisp ridgelines, thin mist in valley, high dynamic range sky, 24mm f/8, ISO 100, tripod, ultra-sharp foreground grass, micro-contrast on rocks"

Prompt: "realism, rainy night city scene with neon reflections, person holding a transparent umbrella, water droplets sharp on umbrella surface, shallow DOF, 55mm f/1.8, ISO 1600, blue and magenta neon, storefront sign reads "OPEN 24/7""

Prompt: "realism, athlete mid-sprint on track, strong sunlight, backlit dust particles, frozen motion at 1/2000s, 200mm f/2.8, ISO 400, muscle definition and sweat droplets detailed, stadium banner says "FINALS""

Prompt: "realism, corporate headshot of a CTO in glass-walled office, city skyline bokeh, balanced key/fill lighting, 85mm f/2, ISO 100, crisp lapel and hair detail, subtle reflection on glasses"

If you have questions or suggestions, join our community:
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