from transformers import AutoConfig, AutoModel import gradio as gr import spaces model_path = "turing-motors/Heron-NVILA-Lite-15B" # or directly from_pretrained model = AutoModel.from_pretrained(model_path, trust_remote_code=True, device_map="auto") # examples generate using generation_config from PIL import Image import requests from transformers import GenerationConfig generation_config = { "max_new_tokens": 2048, "temperature": 0.5, "do_sample": True, } generation_config = GenerationConfig(**generation_config) DESCRIPTION = '''

非公式Heron-NVILA-Lite-15B

Heron-NVILA-Lite-15Bの非公式デモだよ。 turing-motors/Heron-NVILA-Lite-15B.

''' @spaces.GPU() def infer(image): response = model.generate_content( [image, "画像を可能な限り詳細に説明してください。"], generation_config=generation_config ) return response css = """ h1 { text-align: center; display: block; } #col-container { margin: 0 auto; max-width: 520px; } """ with gr.Blocks(fill_height=True, css=css) as demo: with gr.Column(elem_id="col-container"): gr.Markdown(DESCRIPTION) image_input=gr.Image(type="pil", label="画像をアップロード") run_button = gr.Button("画像の説明文を生成する", scale=0) text_output=gr.Textbox(label="生成されたテキスト") run_button.click( fn = infer, inputs = image_input, outputs = text_output, ) if __name__ == "__main__": demo.launch(mcp_server=True)