junnyu
/

stable-diffusion-v1-4-paddle

stable-diffusion

stable-diffusion-diffusers

Model card Files Files and versions Community

junnyu commited on Oct 3, 2022

Commit

9c1ba7f

•

1 Parent(s): 6d9d6ba

Update README.md

Files changed (1) hide show

README.md +4 -4

README.md CHANGED Viewed

@@ -71,9 +71,9 @@ import paddle
 from paddle.amp import auto_cast as autocast
 from diffusers_paddle import StableDiffusionPipeline
-model_id = "CompVis/stable-diffusion-v1-4"
-pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True)
 prompt = "a photo of an astronaut riding a horse on mars"
 with autocast(True):
@@ -89,7 +89,7 @@ If you are limited by GPU memory and have less than 10GB of GPU RAM available, p
 ```py
 import paddle
-pipe = StableDiffusionPipeline.from_pretrained(model_id, paddle_dtype=paddle.float16, use_auth_token=True)
 prompt = "a photo of an astronaut riding a horse on mars"
 with autocast(True):
@@ -106,7 +106,7 @@ from paddle.amp import auto_cast as autocast
 model_id = "junnyu/stable-diffusion-v1-4-paddle"
 # Use the K-LMS scheduler here instead
 scheduler = LMSDiscreteScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", num_train_timesteps=1000)
-pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, use_auth_token=True)
 prompt = "a photo of an astronaut riding a horse on mars"
 with autocast(True):

 from paddle.amp import auto_cast as autocast
 from diffusers_paddle import StableDiffusionPipeline
+model_id = "junnyu/stable-diffusion-v1-4-paddle"
+pipe = StableDiffusionPipeline.from_pretrained(model_id)
 prompt = "a photo of an astronaut riding a horse on mars"
 with autocast(True):
 ```py
 import paddle
+pipe = StableDiffusionPipeline.from_pretrained(model_id, paddle_dtype=paddle.float16)
 prompt = "a photo of an astronaut riding a horse on mars"
 with autocast(True):
 model_id = "junnyu/stable-diffusion-v1-4-paddle"
 # Use the K-LMS scheduler here instead
 scheduler = LMSDiscreteScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", num_train_timesteps=1000)
+pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler)
 prompt = "a photo of an astronaut riding a horse on mars"
 with autocast(True):