Twitter bot that uses NLP models to summarize news articles referenced in a user's twitter timeline
1.) Extracts all tweets from the timeline corresponding to the inputted twitter handle
2.) Uses Google's T5-Transformer to summarize all articles referenced in those tweets
3.) Conducts preliminary semantic analysis on the title of the article.
4.) Displays article details, summary, title sentiment and generates a word cloud based on article content
Sample Output:
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title emoji colorFrom colorTo sdk app_file pinned Belarusian TTS 🐸 green green gradio app.py false Belarusian TTS 📢 🤖 Belarusian TTS (text-to-speec
文字是人类用以记录和表达的最基本工具，也是信息传播的重要媒介。透过文字与符号，我们可以追寻人类文明的起源，可以传播知识与经验，读懂文字是认识与了解的第一步。对于人工智能而言，它的核心问题之一就是认知，而认知的核心则是语义理解。
This is the code of "Scene Text Retrieval via Joint Text Detection and Similarity Learning". For more details, please refer to our CVPR2021 paper.
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🚨 Update 🚨 : As of 2021/10/17, the jiant project is no longer being actively maintained. This means there will be no plans to add new models, tasks,
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