|
import gradio as gr |
|
import os |
|
import spaces |
|
import torch |
|
from diffusers import DiffusionPipeline |
|
|
|
pipe = DiffusionPipeline.from_pretrained("segmind/tiny-sd") |
|
pipe.load_lora_weights( |
|
"philipp-zettl/jon_juarez-lora", |
|
hf_token=os.environ.get('HF_TOKEN') |
|
) |
|
pipe.to('cuda') |
|
@spaces.GPU |
|
def generate(prompt, negative_prompt, num_inference_steps, width, height, num_samples): |
|
return pipe( |
|
prompt, |
|
negative_prompt=negative_prompt, |
|
num_inference_steps=num_inference_steps, |
|
width=width, |
|
height=height, |
|
num_images_per_prompt=num_samples |
|
).images |
|
|
|
|
|
app = gr.Interface( |
|
fn=generate, |
|
inputs=[ |
|
gr.Text(label="Prompt"), |
|
gr.Text("", label="Negative Prompt"), |
|
gr.Slider(minimum=1, maximum=100, value=45, label="Number inference steps"), |
|
gr.Number(512, label='Image width'), |
|
gr.Number(512, label='Image height'), |
|
gr.Slider(minimum=1, maximum=10, value=1, label='Number samples'), |
|
], |
|
outputs=gr.Gallery(), |
|
examples=[ |
|
[ |
|
"Colorful line shading by JON_JUAREZ a dark cave with toxic mushrooms", |
|
"", |
|
45, |
|
512, |
|
512, |
|
1 |
|
] |
|
|
|
|
|
] |
|
) |
|
|
|
app.launch() |
