HighCWu commited on
Commit
1d2fa31
1 Parent(s): a513bb0

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +6 -6
README.md CHANGED
@@ -8,7 +8,7 @@ tags:
8
  - image-to-image
9
  - diffusers
10
  - controlnet
11
- - controllora
12
  ---
13
 
14
  # ControlLoRA - Face Landmarks Version
@@ -37,7 +37,7 @@ from PIL import Image
37
  from diffusers import StableDiffusionControlNetPipeline, UNet2DConditionModel, UniPCMultistepScheduler
38
  import torch
39
  from PIL import Image
40
- from models.controllora import ControlLoRAModel
41
 
42
  image = Image.open('<Your Conditioning Image Path>')
43
 
@@ -46,13 +46,13 @@ base_model = "runwayml/stable-diffusion-v1-5"
46
  unet = UNet2DConditionModel.from_pretrained(
47
  base_model, subfolder="unet", torch_dtype=torch.float16
48
  )
49
- controllora = ControlLoRAModel.from_pretrained(
50
- "HighCWu/sd-controllora-face-landmarks", torch_dtype=torch.float16
51
  )
52
- controllora.tie_weights(unet)
53
 
54
  pipe = StableDiffusionControlNetPipeline.from_pretrained(
55
- base_model, unet=unet, controlnet=controllora, safety_checker=None, torch_dtype=torch.float16
56
  )
57
 
58
  pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
 
8
  - image-to-image
9
  - diffusers
10
  - controlnet
11
+ - control-lora
12
  ---
13
 
14
  # ControlLoRA - Face Landmarks Version
 
37
  from diffusers import StableDiffusionControlNetPipeline, UNet2DConditionModel, UniPCMultistepScheduler
38
  import torch
39
  from PIL import Image
40
+ from models.control_lora import ControlLoRAModel
41
 
42
  image = Image.open('<Your Conditioning Image Path>')
43
 
 
46
  unet = UNet2DConditionModel.from_pretrained(
47
  base_model, subfolder="unet", torch_dtype=torch.float16
48
  )
49
+ control_lora = ControlLoRAModel.from_pretrained(
50
+ "HighCWu/sd-control-lora-face-landmarks", torch_dtype=torch.float16
51
  )
52
+ control_lora.tie_weights(unet)
53
 
54
  pipe = StableDiffusionControlNetPipeline.from_pretrained(
55
+ base_model, unet=unet, controlnet=control_lora, safety_checker=None, torch_dtype=torch.float16
56
  )
57
 
58
  pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)