Spaces:
Running
on
Zero
Running
on
Zero
from lmdeploy import pipeline, GenerationConfig, TurbomindEngineConfig | |
from lmdeploy.vl import load_image | |
import spaces | |
import gradio as gr | |
from PIL import Image | |
import numpy as np | |
pipe = pipeline('gokaygokay/llava-llama3-docci') | |
def create_captions_llava_llama3_docci(image): | |
gen_config = GenerationConfig(repetition_penalty=1.10) | |
image = Image.fromarray(np.uint8(image)).convert('RGB') | |
response = pipe(('describe this image in detail', image), gen_config=gen_config) | |
return response.text | |
css = """ | |
#mkd { | |
height: 500px; | |
overflow: auto; | |
border: 1px solid #ccc; | |
} | |
""" | |
with gr.Blocks(css=css) as demo: | |
gr.HTML("<h1><center>Fine tuned version of xtuner/llava-llama-3-8b-v1_1 on google/docci dataset.<center><h1>") | |
with gr.Tab(label="SD3 Llava Llama3 Captioner"): | |
with gr.Row(): | |
with gr.Column(): | |
input_img = gr.Image(label="Input Picture") | |
submit_btn = gr.Button(value="Submit") | |
output = gr.Text(label="Caption") | |
gr.Examples( | |
[["image1.jpg"], ["image2.jpg"], ["image3.png"]], | |
inputs = [input_img], | |
outputs = [output], | |
fn=create_captions_llava_llama3_docci, | |
label='Try captioning on examples' | |
) | |
submit_btn.click(create_captions_llava_llama3_docci, [input_img], [output]) | |
demo.launch(debug=True) |