Jay Huang commited on
Commit
5d5459a
1 Parent(s): c3f7293

initial commit

Browse files
Files changed (2) hide show
  1. README.md +2 -1
  2. app.py +1 -140
README.md CHANGED
@@ -1,5 +1,5 @@
1
  ---
2
- title: Text-to-Image Gradio Template
3
  emoji: 🖼
4
  colorFrom: purple
5
  colorTo: red
@@ -7,6 +7,7 @@ sdk: gradio
7
  sdk_version: 4.42.0
8
  app_file: app.py
9
  pinned: false
 
10
  ---
11
 
12
  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
1
  ---
2
+ title: Jayhoang Vgirlclub
3
  emoji: 🖼
4
  colorFrom: purple
5
  colorTo: red
 
7
  sdk_version: 4.42.0
8
  app_file: app.py
9
  pinned: false
10
+ license: apache-2.0
11
  ---
12
 
13
  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
app.py CHANGED
@@ -1,142 +1,3 @@
1
  import gradio as gr
2
- import numpy as np
3
- import random
4
- #import spaces #[uncomment to use ZeroGPU]
5
- from diffusers import DiffusionPipeline
6
- import torch
7
 
8
- device = "cuda" if torch.cuda.is_available() else "cpu"
9
- model_repo_id = "stabilityai/sdxl-turbo" #Replace to the model you would like to use
10
-
11
- if torch.cuda.is_available():
12
- torch_dtype = torch.float16
13
- else:
14
- torch_dtype = torch.float32
15
-
16
- pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
17
- pipe = pipe.to(device)
18
-
19
- MAX_SEED = np.iinfo(np.int32).max
20
- MAX_IMAGE_SIZE = 1024
21
-
22
- #@spaces.GPU #[uncomment to use ZeroGPU]
23
- def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, progress=gr.Progress(track_tqdm=True)):
24
-
25
- if randomize_seed:
26
- seed = random.randint(0, MAX_SEED)
27
-
28
- generator = torch.Generator().manual_seed(seed)
29
-
30
- image = pipe(
31
- prompt = prompt,
32
- negative_prompt = negative_prompt,
33
- guidance_scale = guidance_scale,
34
- num_inference_steps = num_inference_steps,
35
- width = width,
36
- height = height,
37
- generator = generator
38
- ).images[0]
39
-
40
- return image, seed
41
-
42
- examples = [
43
- "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
44
- "An astronaut riding a green horse",
45
- "A delicious ceviche cheesecake slice",
46
- ]
47
-
48
- css="""
49
- #col-container {
50
- margin: 0 auto;
51
- max-width: 640px;
52
- }
53
- """
54
-
55
- with gr.Blocks(css=css) as demo:
56
-
57
- with gr.Column(elem_id="col-container"):
58
- gr.Markdown(f"""
59
- # Text-to-Image Gradio Template
60
- """)
61
-
62
- with gr.Row():
63
-
64
- prompt = gr.Text(
65
- label="Prompt",
66
- show_label=False,
67
- max_lines=1,
68
- placeholder="Enter your prompt",
69
- container=False,
70
- )
71
-
72
- run_button = gr.Button("Run", scale=0)
73
-
74
- result = gr.Image(label="Result", show_label=False)
75
-
76
- with gr.Accordion("Advanced Settings", open=False):
77
-
78
- negative_prompt = gr.Text(
79
- label="Negative prompt",
80
- max_lines=1,
81
- placeholder="Enter a negative prompt",
82
- visible=False,
83
- )
84
-
85
- seed = gr.Slider(
86
- label="Seed",
87
- minimum=0,
88
- maximum=MAX_SEED,
89
- step=1,
90
- value=0,
91
- )
92
-
93
- randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
94
-
95
- with gr.Row():
96
-
97
- width = gr.Slider(
98
- label="Width",
99
- minimum=256,
100
- maximum=MAX_IMAGE_SIZE,
101
- step=32,
102
- value=1024, #Replace with defaults that work for your model
103
- )
104
-
105
- height = gr.Slider(
106
- label="Height",
107
- minimum=256,
108
- maximum=MAX_IMAGE_SIZE,
109
- step=32,
110
- value=1024, #Replace with defaults that work for your model
111
- )
112
-
113
- with gr.Row():
114
-
115
- guidance_scale = gr.Slider(
116
- label="Guidance scale",
117
- minimum=0.0,
118
- maximum=10.0,
119
- step=0.1,
120
- value=0.0, #Replace with defaults that work for your model
121
- )
122
-
123
- num_inference_steps = gr.Slider(
124
- label="Number of inference steps",
125
- minimum=1,
126
- maximum=50,
127
- step=1,
128
- value=2, #Replace with defaults that work for your model
129
- )
130
-
131
- gr.Examples(
132
- examples = examples,
133
- inputs = [prompt]
134
- )
135
- gr.on(
136
- triggers=[run_button.click, prompt.submit],
137
- fn = infer,
138
- inputs = [prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
139
- outputs = [result, seed]
140
- )
141
-
142
- demo.queue().launch()
 
1
  import gradio as gr
 
 
 
 
 
2
 
3
+ gr.load("models/jayhoang/vgirlclub").launch()