luisrguerra commited on
Commit
acb7c3b
1 Parent(s): 7e1dc75

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +3 -14
app.py CHANGED
@@ -20,29 +20,18 @@ import gradio_user_history as gr_user_history
20
  from concurrent.futures import ThreadPoolExecutor
21
  import uuid
22
 
23
- DESCRIPTION = '''# Latent Consistency Model OpenVINO CPU
24
- Based on [Latency Consistency Model OpenVINO CPU](https://huggingface.co/spaces/deinferno/Latent_Consistency_Model_OpenVino_CPU) HF space
25
-
26
- Converted from [SoteMix](https://huggingface.co/Disty0/SoteMix) to [LCM_SoteMix](https://huggingface.co/Disty0/LCM_SoteMix) and then to OpenVINO
27
-
28
- This model is for Anime art style.
29
-
30
- Faster but lower quality version with TAESD VAE: [LCM_SoteMix_OpenVINO_CPU_Space_TAESD](https://huggingface.co/spaces/Disty0/LCM_SoteMix_OpenVINO_CPU_Space_TAESD)
31
-
32
- [LCM Project page](https://latent-consistency-models.github.io)
33
-
34
- <p>Running on a Dual Core CPU with OpenVINO Acceleration</p>
35
  '''
36
 
37
  MAX_SEED = np.iinfo(np.int32).max
38
  CACHE_EXAMPLES = os.getenv("CACHE_EXAMPLES") == "1"
39
 
40
- model_id = "Disty0/LCM_SoteMix"
41
  batch_size = -1
42
  width = int(os.getenv("IMAGE_WIDTH", "512"))
43
  height = int(os.getenv("IMAGE_HEIGHT", "512"))
44
  num_images = int(os.getenv("NUM_IMAGES", "1"))
45
- guidance_scale = float(os.getenv("GUIDANCE_SCALE", "1.0"))
46
 
47
  pipe = OVStableDiffusionPipeline.from_pretrained(model_id, compile = False, ov_config = {"CACHE_DIR":""})
48
  pipe.reshape(batch_size=batch_size, height=height, width=width, num_images_per_prompt=num_images)
 
20
  from concurrent.futures import ThreadPoolExecutor
21
  import uuid
22
 
23
+ DESCRIPTION = '''# OpenVINO CPU
 
 
 
 
 
 
 
 
 
 
 
24
  '''
25
 
26
  MAX_SEED = np.iinfo(np.int32).max
27
  CACHE_EXAMPLES = os.getenv("CACHE_EXAMPLES") == "1"
28
 
29
+ model_id = "rubbrband/realDream_11"
30
  batch_size = -1
31
  width = int(os.getenv("IMAGE_WIDTH", "512"))
32
  height = int(os.getenv("IMAGE_HEIGHT", "512"))
33
  num_images = int(os.getenv("NUM_IMAGES", "1"))
34
+ guidance_scale = float(os.getenv("GUIDANCE_SCALE", "5.0"))
35
 
36
  pipe = OVStableDiffusionPipeline.from_pretrained(model_id, compile = False, ov_config = {"CACHE_DIR":""})
37
  pipe.reshape(batch_size=batch_size, height=height, width=width, num_images_per_prompt=num_images)