import gradio as gr
from PIL import Image
import diffusers
import torch
from diffusers import StableDiffusionPipeline
from huggingface_hub import login

login(token="insert your token here")

# Load the model
model_id = "insert your model path like CoWork/fullers-sdv2-1-768-object-fullersamberale001-v1"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to("cuda") 

def inference(prompt, num_samples):
    all_images = [] 
    prompt_update = 'insert your trained concept name like fullersamberale001' + prompt
    images = pipe(prompt_update, num_images_per_prompt=num_samples, num_inference_steps=50, guidance_scale=7.5).images
    all_images.extend(images)
    return all_images

# Create Gradio interface
iface = gr.Interface(
    fn=inference,
    inputs=["textbox", "slider"],
    outputs="gallery",
)

iface.launch()