File size: 2,202 Bytes
685d3ca |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
license: other
license_name: stabilityai-ai-community
license_link: LICENSE.md
language:
- en
base_model:
- stabilityai/stable-diffusion-3.5-medium
pipeline_tag: text-to-image
---
<div align="center">
**TensorArt Stable Diffusion 3.5 Medium ControlNet Depth**
# <img src="./assets/showcase.png"/>
</div>
# With SD3.5M
```python
import torch
from diffusers import StableDiffusion3ControlNetPipeline
from diffusers.models import SD3ControlNetModel
from diffusers.utils import load_image
controlnet = SD3ControlNetModel.from_pretrained("tensorart/SD3.5M-Controlnet-Depth")
pipe = StableDiffusion3ControlNetPipeline.from_pretrained(
"stabilityai/stable-diffusion-3-medium",
controlnet=controlnet
)
pipe.to("cuda", torch.float16)
control_image = load_image("https://huggingface.co/tensorart/SD3.5M-Controlnet-Depth/resolve/main/images/depth.png")
prompt = "A cyberpunk man"
negative_prompt = "low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly, monochrome"
image = pipe(
prompt,
num_inference_steps=30,
negative_prompt=negative_prompt,
control_image=control_image,
guidance_scale=4.5,
).images[0]
image.save('image.jpg')
```
# With TensorArt's SD3.5M Turbo
```python
import torch
from diffusers import StableDiffusion3ControlNetPipeline
from diffusers.models import SD3ControlNetModel
from diffusers.utils import load_image
controlnet = SD3ControlNetModel.from_pretrained("tensorart/SD3.5M-Controlnet-Depth")
pipe = StableDiffusion3ControlNetPipeline.from_pretrained(
"stabilityai/stable-diffusion-3-medium",
controlnet=controlnet
)
pipe.to("cuda", torch.float16)
control_image = load_image("https://huggingface.co/tensorart/SD3.5M-Controlnet-Depth/resolve/main/images/depth.png")
prompt = "A cyberpunk man"
negative_prompt = "low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly, monochrome"
image = pipe(
prompt,
num_inference_steps=8,
negative_prompt=negative_prompt,
control_image=control_image,
guidance_scale=1.5
).images[0]
image.save('image.jpg')
```
|