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import subprocess
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
tokenizer = AutoTokenizer.from_pretrained("ericzhou/DialoGPT-Medium-Rick_v2")
model = AutoModelForCausalLM.from_pretrained("ericzhou/DialoGPT-Medium-Rick_v2")
def predict(input, history=[]):
# tokenize the new input sentence
new_user_input_ids = tokenizer.encode(
input + tokenizer.eos_token, return_tensors="pt"
)
# append the new user input tokens to the chat history
bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
# generate a response
history = model.generate(
bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id
).tolist()
# convert the tokens to text, and then split the responses into the right format
response = tokenizer.decode(history[0]).split("<|endoftext|>")
response = [
(response[i], response[i + 1]) for i in range(0, len(response) - 1, 2)
] # convert to tuples of list
return response, history
import gradio as gr
demo = gr.Blocks()
with demo:
gr.Markdown(
"""
<center>
<img src="https://huggingface.co/spaces/Gradio-Blocks/RickandMorty-BlockParty/resolve/main/img/img1.png" alt="dialog" width="250" height="250">
# Let's start the party with Rick & Morty
Chat with Morty by typing in the input box below.
</center>
"""
)
state = gr.Variable(value=[])
chatbot = gr.Chatbot()
text = gr.Textbox(
label="Talk to Morty here... (press enter to submit)",
value="How are you?",
max_lines=1,
)
text.submit(predict, [text, state], [chatbot, state])
text.submit(lambda x: "", text, text)
demo.launch()
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