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- README.md +4 -4
- app.py +72 -0
- requirements.txt +3 -0
README.md
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---
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title: MarabuTamilDemo
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emoji:
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colorFrom:
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sdk: gradio
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sdk_version: 4.
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app_file: app.py
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pinned: false
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license: gpl-3.0
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---
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title: MarabuTamilDemo
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emoji: 📉
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colorFrom: green
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colorTo: indigo
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sdk: gradio
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sdk_version: 4.16.0
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app_file: app.py
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pinned: false
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license: gpl-3.0
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app.py
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
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from threading import Thread
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import gradio as gr
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class ChatbotService:
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def __init__(self, model_name="RajuKandasamy/marabutamil"):
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self.model = AutoModelForCausalLM.from_pretrained(model_name)
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self.tokenizer = AutoTokenizer.from_pretrained(model_name)
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self.streamer = None
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def call(self, prompt):
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self.streamer = TextIteratorStreamer(self.tokenizer, skip_prompt=True, timeout=5)
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prompt = prompt.replace("<br>", "\n")
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print(prompt)
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inputs = self.tokenizer(prompt, return_tensors="pt")
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print(inputs)
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kwargs = dict(input_ids=inputs["input_ids"], streamer=self.streamer, max_new_tokens=256, do_sample=True, top_p=0.8, top_k=500, temperature=0.001, repetition_penalty=1.4)
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thread = Thread(target=self.model.generate, kwargs=kwargs)
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thread.start()
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return ""
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import gradio as gr
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example_questions = [
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f"""பாடல்:
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நின்றன நின்றன நில்லாகும்""",
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f"""செல்வம் நிலையாமை
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அறத்துப்பால்
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பாடல்:
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துகள்தீர் பெருஞ்செல்வம் தோன்றியக்கால் தொட்டுப்""",
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f"""பாடல்:
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கொங்குதேர் வாழ்க்கை அஞ்சிறைத் தும்பி
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காமம் செப்பாது கண்டது மொழிமோ""",
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f"""வேதம் உரைத்தானும் வேதிய னாகிலன்
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வேதம் உரைத்தானும் வேதா விளங்கிட"""
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]
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chatbot_service = ChatbotService()
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with gr.Blocks() as demo:
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chatbot = gr.Chatbot()
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with gr.Row():
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msg = gr.Textbox(placeholder="Type your message here...", label="Venba first Stanza:")
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run = gr.Button("Run")
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examples_dropdown = gr.Dropdown(choices=example_questions, label="Select an example prompt")
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examples_dropdown.change(fn=lambda x: x, inputs=examples_dropdown, outputs=msg)
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clear = gr.Button("Clear")
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def user(question, user_message, history):
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if history == None:
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history = []
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user_message = question
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return "", history + [[user_message, None]]
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def bot(history):
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#print("Question: ", history[-1][0])
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chatbot_service.call(history[-1][0])
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history[-1][1] = ""
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for character in chatbot_service.streamer:
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print(character)
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history[-1][1] += character
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yield history
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run.click(user, [msg, chatbot], [msg, chatbot], queue=False).then(bot, chatbot, chatbot)
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clear.click(lambda: None, None, chatbot, queue=False)
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demo.queue()
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demo.launch()
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requirements.txt
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torch
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gradio==3.37.0
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transformers==4.37.1
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