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# load important libraries
from datasets import load_dataset
from transformers import AutoModelForSeq2SeqLM
from transformers import AutoTokenizer
from transformers import GenerationConfig
import streamlit as st
# load the dialog summarization dataset
huggingface_dataset_name = "knkarthick/dialogsum"
dataset = load_dataset(huggingface_dataset_name)
# load the google FLAN-T5 base model
model_name='google/flan-t5-base'
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
# load the specific tokenizer for above model
tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
# initialize variables
example_indices_full = [40]
example_indices_full_few_shot = [40, 80, 120, 200, 220]
dash_line = '-'.join('' for x in range(100))
# zero_shot inference
def zero_shot(my_example):
prompt = f"""
Dialogue:
{my_example}
What was going on?
"""
inputs = tokenizer(prompt, return_tensors='pt')
output = tokenizer.decode(
model.generate(
inputs["input_ids"],
max_new_tokens=50
)[0],
skip_special_tokens=True
)
return output
# this prompt template will be used
def my_prompt(example_indices, my_example):
prompt = ''
for index in example_indices:
dialogue = dataset['test'][index]['dialogue']
summary = dataset['test'][index]['summary']
prompt += f"""
Dialogue:
{dialogue}
What was going on?
{summary}
"""
prompt += f"""
Dialogue:
{my_example}
What was going on?
"""
return prompt
# this is for one_shot
def one_shot(example_indices_full,my_example):
inputs = tokenizer(my_prompt(example_indices_full,my_example), return_tensors='pt')
output = tokenizer.decode(
model.generate(
inputs["input_ids"],
max_new_tokens=50
)[0],
skip_special_tokens=True
)
return output
# few_shot
def few_shot(example_indices_full_few_shot,my_example):
inputs = tokenizer(my_prompt(example_indices_full_few_shot,my_example), return_tensors='pt')
output = tokenizer.decode(
model.generate(
inputs["input_ids"],
max_new_tokens=50
)[0],
skip_special_tokens=True
)
return output
st.title("Google FLAN-T5(Base) Prompt Engineered Model: Zero-shot, Single-shot, and Few-shot")
my_example = st.text_area("Enter dialogues to summarize", value="Maaz: Jalal how are you?\nJalal: I am good thank you.\nMaaz: Are you going to school tomorrow.\nJalal: No bro i am not going to school tomorrow.\nMaaz: why?\nJalal: I am working on a project, are you want to work with me on my project?\nMaaz: sorry, i have to go to school.")
if st.button("Run"):
zero_shot_output = zero_shot(my_example)
one_shot_output = one_shot(example_indices_full, my_example)
few_shot_output = few_shot(example_indices_full_few_shot, my_example)
st.header("**Comparison of Outputs**")
# Create three columns
col1, col2, col3 = st.columns(3)
# Display outputs in respective columns
with col1:
st.subheader("Zero-shot Output")
st.write(zero_shot_output)
with col2:
st.subheader("One-shot Output")
st.write(one_shot_output)
with col3:
st.subheader("Few-shot Output")
st.write(few_shot_output) |