42 lines
2.1 KiB
Markdown
42 lines
2.1 KiB
Markdown
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# T5 One Line Summary⚡️
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A T5 model trained on 370,000 research papers, to generate one line summary based on description/abstract of the papers
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## Usage
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```python
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model_name="snrspeaks/t5-one-line-summary"
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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abstract="""We describe a system called Overton, whose main design goal is to support engineers
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in building, monitoring, and improving production machine learning systems. Key challenges engineers
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face are monitoring fine-grained quality, diagnosing errors in sophisticated applications, and
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handling contradictory or incomplete supervision data. Overton automates the life cycle of model
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construction, deployment, and monitoring by providing a set of novel high-level, declarative abstractions.
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Overton's vision is to shift developers to these higher-level tasks instead of lower-level machine learning tasks.
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In fact, using Overton, engineers can build deep-learning-based applications without writing any code
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in frameworks like TensorFlow. For over a year, Overton has been used in production to support multiple
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applications in both near-real-time applications and back-of-house processing.
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In that time, Overton-based applications have answered billions of queries in multiple
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languages and processed trillions of records reducing errors 1.7-2.9 times versus production systems.
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"""
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input_ids = tokenizer.encode("summarize: " + abstract, return_tensors="pt", add_special_tokens=True)
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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)
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preds = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=True) for g in generated_ids]
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print(preds)
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# output
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['Overton: Building, Deploying, and Monitoring Machine Learning Systems for Engineers',
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'Overton: A System for Building, Monitoring, and Improving Production Machine Learning Systems',
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'Overton: Building, Monitoring, and Improving Production Machine Learning Systems']
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```
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