multimodalart HF staff commited on
Commit
fea7223
1 Parent(s): c5bfed7

Update to the final API naming

Browse files
Files changed (1) hide show
  1. app.py +3 -3
app.py CHANGED
@@ -1,16 +1,16 @@
1
- from diffusers import LatentDiffusionPipeline
2
  import gradio as gr
3
  import PIL.Image
4
  import numpy as np
5
  import random
6
  import torch
7
 
8
- ldm_pipeline = LatentDiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256")
9
 
10
  def predict(prompt, steps=100, seed=42, guidance_scale=6.0):
11
  torch.cuda.empty_cache()
12
  generator = torch.manual_seed(seed)
13
- images = ldm_pipeline([prompt], generator=generator, num_inference_steps=steps, eta=0.3, guidance_scale=guidance_scale)
14
  return images[0]
15
 
16
  random_seed = random.randint(0, 2147483647)
 
1
+ from diffusers import LDMTextToImagePipeline
2
  import gradio as gr
3
  import PIL.Image
4
  import numpy as np
5
  import random
6
  import torch
7
 
8
+ ldm_pipeline = LDMTextToImagePipeline.from_pretrained("CompVis/ldm-text2im-large-256")
9
 
10
  def predict(prompt, steps=100, seed=42, guidance_scale=6.0):
11
  torch.cuda.empty_cache()
12
  generator = torch.manual_seed(seed)
13
+ images = ldm_pipeline([prompt], generator=generator, num_inference_steps=steps, eta=0.3, guidance_scale=guidance_scale)["sample"]
14
  return images[0]
15
 
16
  random_seed = random.randint(0, 2147483647)