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import os |
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import gradio as gr |
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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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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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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import torch |
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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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def predict(input): |
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new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt') |
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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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response = tokenizer.decode(history[0]).split("<|endoftext|>") |
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return response[1] |
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gr.Interface(fn = predict, inputs = ["textbox"], outputs = ["text"], title = title, description = description, article = article).launch() |
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