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Create app.py
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app.py
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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import gradio as gr
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import os
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# Initialize the Qwen model and tokenizer
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tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-1_8B-Chat", trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-1_8B-Chat", device_map="auto", trust_remote_code=True).eval()
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class ChatBot:
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def __init__(self):
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self.history = None
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def predict(self, user_input, system_prompt=""):
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response, self.history = model.chat(tokenizer, user_input, history=self.history, system=system_prompt)
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return response
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bot = ChatBot()
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title = "👋🏻Welcome to🌟Tonic's🦆Qwen📲On-Device🗣️Chat!"
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description = """
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You can use this Space to test out the current model [Qwen/Qwen-1_8B-Chat](https://huggingface.co/Qwen/Qwen-1_8B-Chat) You can also use 🧑🏻🚀Qwen/Qwen-1_8B-Chat🚀 by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic1/wen-1_8B-Chat?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3>
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Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community on 👻Discord: [Discord](https://discord.gg/nXx5wbX9) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [PolyGPT](https://github.com/tonic-ai/polygpt-alpha)
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"""
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examples = [["Hello, how are you today?"]]
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iface = gr.Interface(
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fn=bot.predict,
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title=title,
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description=description,
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examples=examples,
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inputs=["text", "text"], # User input and system prompt
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outputs="text",
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theme="default"
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)
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iface.launch()
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