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TwitterをスクレイピングしてLSTMに学習させた発言をランダムに生成するウェブアプリ

Python 64.80% HTML 12.96% Dockerfile 22.25%

abetter's Introduction

Abetter

TwitterをスクレイピングしてLSTMに学習させた発言をランダムに生成するウェブアプリ

環境:

  • Docker
  • Python3.6
  • PyTorch
  • Flask

外部で学習させた重みをFlaskのウェブアプリで使用可能にしています。

モデルはLSTMです。

使用方法

  1. git clone this/repo
  2. cd abetter
  3. docker build -t container:1.0 .
  4. docker run -it -p 5000:5000 -v ~path/to/repo:/abetter container:1.0
  5. Docker内部へ移動
  6. cd abetter
  7. flask run --host 0.0.0.0 表示されたURLにブラウザでアクセス

あとはご自由にお楽しみください。 モデルの精度は今後LSTM以外を使ったりして改善していく予定です。

参考記事

モデルの読み込み https://qiita.com/derodero24/items/f4cc46f144f404054501

Flaskで自然言語処理アプリの作成 https://qiita.com/oreyutarover/items/909d614ca3b48d2c9e16

ポート開放でハマった所の解決策 https://stackoverflow.com/questions/30323224/deploying-a-minimal-flask-app-in-docker-server-connection-issues

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