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Update app.py
#24
by
Aditibaheti
- opened
app.py
CHANGED
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@@ -1,19 +1,19 @@
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import spaces
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import gradio as gr
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import numpy as np
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import random
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from diffusers import DiffusionPipeline
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import torch
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from huggingface_hub import login
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import os
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# Set your Hugging Face token
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HUGGINGFACE_TOKEN = os.getenv("HUGGINGFACE_TOKEN")
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if HUGGINGFACE_TOKEN is None:
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raise ValueError("Hugging Face token not found. Please set the HUGGINGFACE_TOKEN environment variable.")
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login(token=HUGGINGFACE_TOKEN)
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# Path to your model repository and safetensors weights
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@@ -28,16 +28,11 @@ pipeline = DiffusionPipeline.from_pretrained(
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)
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pipeline.load_lora_weights(lora_weights_path)
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# Comment out the line for sequential CPU offloading
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# pipeline.enable_sequential_cpu_offload()
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pipeline = pipeline.to(device)
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MAX_SEED = np.iinfo(np.int32).max
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MAX_IMAGE_SIZE = 1024 # Reduce max image size to fit within memory constraints
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CACHE_EXAMPLES = False
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@spaces.GPU
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def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
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if randomize_seed:
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@@ -71,6 +66,7 @@ body {
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margin: 0;
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padding: 0;
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}
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#header {
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background-color: #ff3f6c; /* Myntra's pink color */
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color: white;
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@@ -79,6 +75,7 @@ body {
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font-size: 24px;
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font-weight: bold;
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}
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#col-container {
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margin: 0 auto;
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max-width: 720px;
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@@ -87,6 +84,7 @@ body {
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border-radius: 8px;
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box-shadow: 0 2px 8px rgba(0,0,0,0.1);
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}
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.gr-button {
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background-color: #ff3f6c; /* Myntra's pink color */
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color: white;
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@@ -97,17 +95,21 @@ body {
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cursor: pointer;
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margin-top: 10px;
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}
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.gr-button:hover {
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background-color: #e62e5c; /* Darker shade for hover effect */
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}
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.gr-textbox, .gr-slider, .gr-checkbox, .gr-accordion {
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margin-bottom: 20px;
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}
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.gr-markdown {
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text-align: center;
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font-size: 24px;
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margin-bottom: 20px;
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}
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.gr-image {
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border: 1px solid #ebebeb;
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border-radius: 8px;
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@@ -194,10 +196,11 @@ with gr.Blocks(css=css) as demo:
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)
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gr.Examples(
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examples=examples,
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inputs=[prompt],
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outputs=[result],
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)
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run_button.click(
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import spaces
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import os
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import random
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import gradio as gr
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import numpy as np
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from diffusers import DiffusionPipeline
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import torch
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from huggingface_hub import login
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device = "cuda" if torch.cuda.is_available() else "cpu"
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# Set your Hugging Face token
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HUGGINGFACE_TOKEN = os.getenv("HUGGINGFACE_TOKEN")
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login(token=HUGGINGFACE_TOKEN)
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# Path to your model repository and safetensors weights
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)
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pipeline.load_lora_weights(lora_weights_path)
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pipeline = pipeline.to(device)
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MAX_SEED = np.iinfo(np.int32).max
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MAX_IMAGE_SIZE = 1024 # Reduce max image size to fit within memory constraints
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@spaces.GPU
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def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
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if randomize_seed:
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margin: 0;
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padding: 0;
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}
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+
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#header {
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background-color: #ff3f6c; /* Myntra's pink color */
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color: white;
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font-size: 24px;
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font-weight: bold;
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}
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+
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#col-container {
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margin: 0 auto;
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max-width: 720px;
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border-radius: 8px;
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box-shadow: 0 2px 8px rgba(0,0,0,0.1);
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}
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.gr-button {
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background-color: #ff3f6c; /* Myntra's pink color */
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color: white;
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cursor: pointer;
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margin-top: 10px;
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}
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.gr-button:hover {
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background-color: #e62e5c; /* Darker shade for hover effect */
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}
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+
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.gr-textbox, .gr-slider, .gr-checkbox, .gr-accordion {
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margin-bottom: 20px;
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}
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.gr-markdown {
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text-align: center;
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font-size: 24px;
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margin-bottom: 20px;
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}
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.gr-image {
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border: 1px solid #ebebeb;
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border-radius: 8px;
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)
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gr.Examples(
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examples=examples,
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inputs=[prompt],
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outputs=[result],
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fn=infer,
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cache_examples=True,
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)
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run_button.click(
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