import gradio as gr import spaces from transformers import AutoModelForCausalLM, AutoProcessor import torch from PIL import Image import subprocess subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True) models = { "microsoft/Phi-3.5-vision-instruct": AutoModelForCausalLM.from_pretrained("microsoft/Phi-3.5-vision-instruct", trust_remote_code=True, torch_dtype="auto", _attn_implementation="flash_attention_2").cuda().eval() } processors = { "microsoft/Phi-3.5-vision-instruct": AutoProcessor.from_pretrained("microsoft/Phi-3.5-vision-instruct", trust_remote_code=True) } kwargs = {} kwargs['torch_dtype'] = torch.bfloat16 user_prompt = '<|user|>\n' assistant_prompt = '<|assistant|>\n' prompt_suffix = "<|end|>\n" @spaces.GPU def run_example(image, text_input=None, model_id="microsoft/Phi-3.5-vision-instruct"): model = models[model_id] processor = processors[model_id] prompt = f"{user_prompt}<|image_1|>\n{text_input}{prompt_suffix}{assistant_prompt}" image = Image.fromarray(image).convert("RGB") inputs = processor(prompt, image, return_tensors="pt").to("cuda:0") generate_ids = model.generate(**inputs, max_new_tokens=1000, eos_token_id=processor.tokenizer.eos_token_id, ) generate_ids = generate_ids[:, inputs['input_ids'].shape[1]:] response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] return response css = """ footer { visibility: hidden; } """ with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as demo: with gr.Tab(label="Phi-3.5 Input"): with gr.Row(): with gr.Column(): input_img = gr.Image(label="Input Picture") model_selector = gr.Dropdown(choices=list(models.keys()), label="Model", value="microsoft/Phi-3.5-vision-instruct") text_input = gr.Textbox(label="Question") submit_btn = gr.Button(value="Submit") with gr.Column(): output_text = gr.Textbox(label="Output Text") submit_btn.click(run_example, [input_img, text_input, model_selector], [output_text]) demo.queue(api_open=False) demo.launch(debug=True, show_api=False)