A simple Google Colab notebook which can translate an original video into multiple languages along with lip sync.

1、人工智能学习相关资料整理 2、人工智能学习相关示例代码整理，包括tensorflow1.x、tensorflow2.x、pytorch实现 3、提供人工智能常用小工具，例如爬虫、自动化中英文翻译等。4、业务模块的技术方案梳理

Tensorflow v2.6により、サンプル「アテンションを用いたニューラル機械翻訳」 （nmt_with_attention.ipynb）をMecabによる分かち書きを追加して日英翻訳できるようにしたものです。jupyter/tensorflow-notebookコンテナに、Mecab ipadic neologdを追加インストールしたコンテナを作成して使用しています。

Jupyter Notebook - Annotations SDN

Translate Jupyter Notebook file using Bing Translator API.

Translate Markdown files from one language to another using OpenAI's API while retaining original formatting. This Jupyter notebook tokenizes input text, splits into chunks, translates with OpenAI, and reconstructs output to preserve Markdown structure. Useful for localizing documentation, articles, books, and other long-form Markdown content.

A demo notebook for using argos translate

Jupyter notebook used to generate the fine-tuned models for korean natural language processing

This project is a Jupyter Notebook-based application that allows users to translate text into different languages (English, Chinese, and Japanese) or chat with an AI model. The notebook utilizes the Qwen/Qwen2-1.5B-Instruct language model for natural language processing tasks and the gTTS library for text-to-speech conversion.

Notes on ML and DL with jupyter notebooks (python)

A collection of notebooks providing examples on NLP using PyTorch

this is simple translation website using tensorflow transformer model

This project is all about a language translator using Googletrans library with python written in jupyter notebook

This repository contains Jupyter notebooks demonstrating various generation tasks with Large Language Models (LLMs). It provides examples for summarization, text generation, few-shot learning, and translation, utilizing different LLM APIs to showcase the capabilities of multiple providers.

Natural LangWiz is a repository for exploring Natural Language Processing (NLP) techniques through Jupyter notebooks. It covers everything from text preprocessing and sentiment analysis to advanced transformer models. Dive in to see how we turn raw text into actionable insights with a touch of NLP wizardry!