aliabd HF staff commited on
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e757dfc
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Create app.py

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  1. app.py +31 -0
app.py ADDED
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+ import os
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+ import gradio as gr
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+
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+ title = "Ask Rick a Question"
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+ description = """
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+ <center>
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+ The bot was trained to answer questions based on Rick and Morty dialogues. Ask Rick anything!
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+ <img src="https://huggingface.co/spaces/course-demos/Rick_and_Morty_QA/resolve/main/rick.png" width=200px>
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+ </center>
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+ """
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+
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+ article = "Check out [the original Rick and Morty Bot](https://huggingface.co/spaces/kingabzpro/Rick_and_Morty_Bot) that this demo is based off of."
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+
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ import torch
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+
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+ tokenizer = AutoTokenizer.from_pretrained("ericzhou/DialoGPT-Medium-Rick_v2")
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+ model = AutoModelForCausalLM.from_pretrained("ericzhou/DialoGPT-Medium-Rick_v2")
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+
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+ def predict(input):
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+ # tokenize the new input sentence
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+ new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')
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+
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+ # generate a response
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+ history = model.generate(new_user_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id).tolist()
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+
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+ # convert the tokens to text, and then split the responses into the right format
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+ response = tokenizer.decode(history[0]).split("<|endoftext|>")
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+ return response[1]
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+
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+ gr.Interface(fn = predict, inputs = ["textbox"], outputs = ["text"], title = title, description = description, article = article).launch()