Sana_600M_1024px_ControlNet_HED

151
2 languages
—
by
Efficient-Large-Model
Image Model
OTHER
2410.10629B params
New
151 downloads
Early-stage
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Edge AI:
Mobile
Laptop
Server
5388GB+ RAM
Mobile
Laptop
Server
Quick Summary

AI model with specialized capabilities.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
2245GB+ RAM

Code Examples

How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)
How to Usepythonpytorch
import torch
from PIL import Image
from app.sana_controlnet_pipeline import SanaControlNetPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"

pipe = SanaControlNetPipeline("configs/sana_controlnet_config/Sana_600M_img1024_controlnet.yaml")
pipe.from_pretrained("hf://Efficient-Large-Model/Sana_600M_1024px_ControlNet_HED/checkpoints/Sana_600M_1024px_ControlNet_HED.pth")

ref_image = Image.open("asset/controlnet/ref_images/A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a la.jpg")
prompt = "A transparent sculpture of a duck made out of glass. The sculpture is in front of a painting of a landscape."

images = pipe(
    prompt=prompt,
    ref_image=ref_image,
    guidance_scale=4.5,
    num_inference_steps=10,
    sketch_thickness=2,
    generator=torch.Generator(device=device).manual_seed(0),
)

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