t5-one-line-summary/README.md

T5 One Line Summary⚡️

A T5 model trained on 370,000 research papers, to generate one line summary based on description/abstract of the papers

Usage

model_name="snrspeaks/t5-one-line-summary"

from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

abstract="""We describe a system called Overton, whose main design goal is to support engineers 
in building, monitoring, and improving production machine learning systems. Key challenges engineers 
face are monitoring fine-grained quality, diagnosing errors in sophisticated applications, and 
handling contradictory or incomplete supervision data. Overton automates the life cycle of model 
construction, deployment, and monitoring by providing a set of novel high-level, declarative abstractions. 
Overton's vision is to shift developers to these higher-level tasks instead of lower-level machine learning tasks. 
In fact, using Overton, engineers can build deep-learning-based applications without writing any code 
in frameworks like TensorFlow. For over a year, Overton has been used in production to support multiple 
applications in both near-real-time applications and back-of-house processing. 
In that time, Overton-based applications have answered billions of queries in multiple 
languages and processed trillions of records reducing errors 1.7-2.9 times versus production systems.
"""

input_ids = tokenizer.encode("summarize: " + abstract, return_tensors="pt", add_special_tokens=True)

generated_ids = model.generate(input_ids=input_ids, num_beams=5, max_length=50, repetition_penalty=2.5, length_penalty=1, early_stopping=True, num_return_sequences=3)

preds = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=True) for g in generated_ids]

print(preds)

# output

['Overton: Building, Deploying, and Monitoring Machine Learning Systems for Engineers',

 'Overton: A System for Building, Monitoring, and Improving Production Machine Learning Systems',

 'Overton: Building, Monitoring, and Improving Production Machine Learning Systems']