Spaces:
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FEAT: first commit
Browse files- README.md +3 -1
- app.py +198 -0
- examples/1.jpg +0 -0
- examples/2.jpg +0 -0
- examples/3.jpg +0 -0
- examples/example_inputs.jsonl +3 -0
- requirements.txt +3 -0
- style.css +7 -0
README.md
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@@ -3,7 +3,9 @@ title: Ziya BLIP2 14B Visual V1 Demo
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emoji: 😻
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colorFrom: gray
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colorTo: red
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pinned: false
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license: apache-2.0
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---
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emoji: 😻
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colorFrom: gray
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colorTo: red
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sdk: gradio
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sdk_version: 3.27.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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app.py
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#!/usr/bin/env python
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# this code modify from https://huggingface.co/spaces/lykeven/visualglm-6b
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import gradio as gr
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import re
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from PIL import Image
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import torch
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from io import BytesIO
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import hashlib
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import os
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from transformers import LlamaForCausalLM, LlamaTokenizer, BlipImageProcessor, BitsAndBytesConfig, AutoModelForCausalLM
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DESCRIPTION = '''# <a href="https://huggingface.co/IDEA-CCNL/Ziya-BLIP2-14B-Visual-v1">Ziya-Blip2-14B</a>'''
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MAINTENANCE_NOTICE1 = 'Hint 1: If the app report "Something went wrong, connection error out", please turn off your proxy and retry.\nHint 2: If you upload a large size of image like 10MB, it may take some time to upload and process. Please be patient and wait.'
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MAINTENANCE_NOTICE2 = '提示1: 如果应用报了“Something went wrong, connection error out”的错误,请关闭代理并重试。\n提示2: 如果你上传了很大的图片,比如10MB大小,那将需要一些时间来上传和处理,请耐心等待。'
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NOTES = 'This app is adapted from <a href="https://huggingface.co/IDEA-CCNL/Ziya-BLIP2-14B-Visual-v1">https://huggingface.co/IDEA-CCNL/Ziya-BLIP2-14B-Visual-v1</a>. It would be recommended to check out the repo if you want to see the detail of our model. And most of the codes attach to this demo are modify from <a href="https://huggingface.co/spaces/lykeven/visualglm-6b">lykeven/visualglm-6b</a>.'
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import json
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default_chatbox = []
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def is_chinese(text):
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zh_pattern = re.compile(u'[\u4e00-\u9fa5]+')
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return zh_pattern.search(text)
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AUTH_TOKEN = os.getenv("AUTH_TOKEN")
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LM_MODEL_PATH = "gxy/Ziya-LLaMA-13B-v1"
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lm_model = LlamaForCausalLM.from_pretrained(
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LM_MODEL_PATH,
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device_map="auto",
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torch_dtype=torch.float16,
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use_auth_token=AUTH_TOKEN,
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quantization_config=BitsAndBytesConfig(load_in_8bit=True))
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tokenizer = LlamaTokenizer.from_pretrained(LM_MODEL_PATH)
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# visual model
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OPENAI_CLIP_MEAN = [0.48145466, 0.4578275, 0.40821073]
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OPENAI_CLIP_STD = [0.26862954, 0.26130258, 0.27577711]
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# demo.py is in the project path, so we can use local path ".". Otherwise you should use "IDEA-CCNL/Ziya-BLIP2-14B-Visual-v1"
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model = AutoModelForCausalLM.from_pretrained(
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"IDEA-CCNL/Ziya-BLIP2-14B-Visual-v1",
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trust_remote_code=True,
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torch_dtype=torch.float16)
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model.cuda() # if you use on cpu, comment this line
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model.language_model = lm_model
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image_size = model.config.vision_config.image_size
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image_processor = BlipImageProcessor(
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size={"height": image_size, "width": image_size},
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image_mean=OPENAI_CLIP_MEAN,
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image_std=OPENAI_CLIP_STD,
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)
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def post(
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input_text,
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temperature,
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top_p,
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image_prompt,
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result_previous,
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hidden_image
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):
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result_text = [(ele[0], ele[1]) for ele in result_previous]
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previous_querys = []
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previous_outputs = []
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for i in range(len(result_text)-1, -1, -1):
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if result_text[i][0] == "":
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del result_text[i]
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else:
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previous_querys.append(result_text[i][0])
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previous_outputs.append(result_text[i][1])
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is_zh = is_chinese(input_text)
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if image_prompt is None:
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print("Image empty")
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if is_zh:
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result_text.append((input_text, '图片为空!请上传图片并重试。'))
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else:
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result_text.append((input_text, 'Image empty! Please upload a image and retry.'))
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return input_text, result_text, hidden_image
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elif input_text == "":
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print("Text empty")
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result_text.append((input_text, 'Text empty! Please enter text and retry.'))
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return "", result_text, hidden_image
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generate_config = {
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"max_new_tokens": 128,
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"top_p": top_p,
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"temperature": temperature,
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"repetition_penalty": 1.18,
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}
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img = Image.open(image_prompt)
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pixel_values = image_processor(
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img,
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return_tensors="pt").pixel_values.to(
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model.device).to(model.dtype)
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output_buffer = BytesIO()
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img.save(output_buffer, "PNG")
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byte_data = output_buffer.getvalue()
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md = hashlib.md5()
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md.update(byte_data)
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img_hash = md.hexdigest()
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if img_hash != hidden_image:
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previous_querys = []
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previous_outputs = []
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result_text = []
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answer = model.chat(
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tokenizer=tokenizer,
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pixel_values=pixel_values,
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query=input_text,
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previous_querys=previous_querys,
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previous_outputs=previous_outputs,
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**generate_config,
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)
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result_text.append((input_text, answer))
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print(result_text)
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return "", result_text, img_hash
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def clear_fn(value):
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return "", default_chatbox, None
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def clear_fn2(value):
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return default_chatbox
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def io_fn(a, b, c):
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print(f"call io_fn")
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return a, b
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def change_language(value):
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if value == "Change hint to English":
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return "提示变为中文", MAINTENANCE_NOTICE1
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else:
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return "Change hint to English", MAINTENANCE_NOTICE2
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def main():
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gr.close_all()
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examples = []
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with open("./examples/example_inputs.jsonl") as f:
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for line in f:
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data = json.loads(line)
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examples.append(data)
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with gr.Blocks(css='style.css') as demo:
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with gr.Row():
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with gr.Column(scale=4.5):
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with gr.Group():
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input_text = gr.Textbox(label='Input Text', placeholder='Please enter text prompt below and press ENTER.')
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with gr.Row():
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run_button = gr.Button('Generate')
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clear_button = gr.Button('Clear')
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image_prompt = gr.Image(type="filepath", label="Image Prompt", value=None)
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with gr.Row():
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temperature = gr.Slider(maximum=1, value=0.7, minimum=0, label='Temperature')
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top_p = gr.Slider(maximum=1, value=0.1, minimum=0, label='Top P')
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with gr.Group():
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with gr.Row():
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with gr.Column(scale=7):
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maintenance_notice = gr.Markdown(MAINTENANCE_NOTICE1)
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with gr.Column(scale=2):
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change_button = gr.Button('Change hint to English', visible=False)
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with gr.Column(scale=5.5):
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result_text = gr.components.Chatbot(label='Multi-round conversation History', value=[]).style(height=550)
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hidden_image_hash = gr.Textbox(visible=False)
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gr_examples = gr.Examples(examples=[[example["text"], example["image"]] for example in examples],
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inputs=[input_text, image_prompt],
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label="Example Inputs (Click to insert an examplet into the input box)",
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examples_per_page=3)
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gr.Markdown(NOTES)
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print(gr.__version__)
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run_button.click(fn=post,inputs=[input_text, temperature, top_p, image_prompt, result_text, hidden_image_hash],
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outputs=[input_text, result_text, hidden_image_hash])
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input_text.submit(fn=post,inputs=[input_text, temperature, top_p, image_prompt, result_text, hidden_image_hash],
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outputs=[input_text, result_text, hidden_image_hash])
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clear_button.click(fn=clear_fn, inputs=clear_button, outputs=[input_text, result_text, image_prompt])
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image_prompt.upload(fn=clear_fn2, inputs=clear_button, outputs=[result_text])
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image_prompt.clear(fn=clear_fn2, inputs=clear_button, outputs=[result_text])
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print(gr.__version__)
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demo.queue(concurrency_count=10)
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demo.launch(server_name="0.0.0.0")
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if __name__ == '__main__':
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main()
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examples/1.jpg
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examples/2.jpg
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examples/3.jpg
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examples/example_inputs.jsonl
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{"id":1, "text": "这是什么游戏", "image": "examples/1.jpg"}
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{"id":2, "text": "这张图描述了什么", "image": "examples/2.jpg"}
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{"id":3, "text": "这张图有什么奇怪的地方", "image": "examples/3.jpg"}
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requirements.txt
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transformers
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torch
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https://github.com/GGGGGGXY/bitsandbytes/releases/download/0.39/bitsandbytes-0.39.0-py3-none-any.whl
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style.css
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h1 {
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text-align: center;
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}
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img#visitor-badge {
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display: block;
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margin: auto;
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}
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