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import gradio as gr
from transformers import pipeline
import torch
# Maximize CPU usage
torch.set_num_threads(torch.get_num_threads() * 2)
model1 = gr.load("models/Jonny001/NSFW_master")
model2 = gr.load("models/Jonny001/Alita-v1")
model3 = gr.load("models/lexa862/NSFWmodel")
model4 = gr.load("models/Keltezaa/flux_pussy_NSFW")
model5 = gr.load("models/prashanth970/flux-lora-uncensored")
def generate_images(text, selected_model):
if selected_model == "Model 1 (NSFW Master)":
model = model1
elif selected_model == "Model 2 (Alita)":
model = model2
elif selected_model == "Model 3 (Lexa NSFW)":
model = model3
elif selected_model == "Model 4 (Flux NSFW)":
model = model4
elif selected_model == "Model 5 (Lora Uncensored)":
model = model5
else:
return "Invalid model selection."
results = []
for i in range(3):
modified_text = f"{text} variation {i+1}"
result = model(modified_text)
results.append(result)
return results
interface = gr.Interface(
fn=generate_images,
inputs=[
gr.Textbox(label="Type here your imagination:", placeholder="Type your prompt..."),
gr.Radio(
["Model 1 (NSFW Master)", "Model 2 (Alita)", "Model 3 (Lexa NSFW)", "Model 4 (Flux NSFW)", "Model 5 (Lora Uncensored)"],
label="Select Model (Try All Models & Get Different Results)",
value="Model 1 (NSFW Master)",
),
],
outputs=[
gr.Image(label="Generated Image 1"),
gr.Image(label="Generated Image 2"),
gr.Image(label="Generated Image 3"),
],
theme="Yntec/HaleyCH_Theme_Orange",
description="⚠ Sorry for the inconvenience. The models are currently running on the CPU, which might affect performance. We appreciate your understanding.",
cache_examples=False,
)
interface.launch()
# import gradio as gr
# from transformers import pipeline
# import torch
# # Maximize CPU usage
# torch.set_num_threads(torch.get_num_threads() * 2)
# # Load models using Hugging Face pipelines
# model1 = pipeline("text-to-image", model="Jonny001/NSFW_master", device_map="auto")
# model2 = pipeline("text-to-image", model="Jonny001/Alita-v1", device_map="auto")
# model3 = pipeline("text-to-image", model="lexa862/NSFWmodel", device_map="auto")
# model4 = pipeline("text-to-image", model="Keltezaa/flux_pussy_NSFW", device_map="auto")
# model5 = pipeline("text-to-image", model="prashanth970/flux-lora-uncensored", device_map="auto")
# # Function to generate images
# def generate_images(text, selected_model):
# models = {
# "Model 1 (NSFW Master)": model1,
# "Model 2 (Alita)": model2,
# "Model 3 (Lexa NSFW)": model3,
# "Model 4 (Flux NSFW)": model4,
# "Model 5 (Lora Uncensored)": model5,
# }
# model = models.get(selected_model, model1)
# results = []
# for i in range(3):
# modified_text = f"{text} variation {i+1}"
# result = model(modified_text)
# results.append(result)
# return results
# # Gradio interface
# interface = gr.Interface(
# fn=generate_images,
# inputs=[
# gr.Textbox(label="Type here your imagination:", placeholder="Type your prompt..."),
# gr.Radio(
# ["Model 1 (NSFW Master)", "Model 2 (Alita)", "Model 3 (Lexa NSFW)", "Model 4 (Flux NSFW)", "Model 5 (Lora Uncensored)"],
# label="Select Model (Try All Models & Get Different Results)",
# value="Model 1 (NSFW Master)",
# ),
# ],
# outputs=[
# gr.Image(label="Generated Image 1"),
# gr.Image(label="Generated Image 2"),
# gr.Image(label="Generated Image 3"),
# ],
# theme="Yntec/HaleyCH_Theme_Orange",
# description="⚠ Models are running on CPU for optimized performance. Your patience is appreciated!",
# cache_examples=False,
# )
# # Launch the interface
# interface.launch()
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