Shivanand Roy 👋
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README.md
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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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```python
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model_name = "snrspeaks/t5-one-line-summary"
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---
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datasets:
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- arxiv
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tags:
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- summarization
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widget:
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- text: "summarize: 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."
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license: mit
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---
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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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Trained with [**simpleT5**](https://https://github.com/Shivanandroy/simpleT5)⚡️in just 3 lines of code
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> [**simpleT5**](https://https://github.com/Shivanandroy/simpleT5)⚡️ is a python package built on top of **pytorch lightning** and **transformers**🤗, to quickly train T5 models.
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## Usage:[](https://colab.research.google.com/drive/1HrfT8IKLXvZzPFpl1EhZ3s_iiXG3O2VY?usp=sharing)
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```python
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model_name = "snrspeaks/t5-one-line-summary"
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