1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.
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Updated
May 21, 2024 - Python
1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.
HMS ML Demo provides an example of integrating Huawei ML Kit service into applications. This example demonstrates how to integrate services provided by ML Kit, such as face detection, text recognition, image segmentation, asr, and tts.
A free google translation api, support text and page
HUAWEI HMS meachine learning services demo apk download.
Add online and offline text translation to Android apps
CLI utility for everyday tasks. With getme you get weather, forecast, currency rate, upload files, IP address, word definitions, text translations, internet speed, do google searches, get inspirational quotes and get Chuck Norris jokes
Paper list of simultaneous translation / streaming translation, including text-to-text machine translation and speech-to-text translation.
Text translation library with wrappers for Google Translate, My memory and more...
Samples for fine-tuning HuggingFace models with AzureML
Combines the LEGO Mindstorms 51515 with the NVIDIA Jetson Nano
Chatter Box is an android app that is capable of Voice, Text, Image Text Translation, and end-to-end chat translation.
Live Multi-lingual Communication
A simple javascript library for translating web content.
Instant message applicaiton with automatic translation mecanism
Natural Language Processing First Steps with Python
A hobby project. Online translator service. This service helps you to translate a text or speech from any languages in the world to any other.
A simple application which demos Azure cognitive services Bing Speech API and Text Translator API
Elixir package for interaction with Yandex.Translate API
Cloud based community-centered multilingual communication platform with Discussion Forum and image, text translation capabiities.
This is a machine learning based project that accepts user reports in Arabic and classifies them into one of four categories: car accidents, crime, fire, and robbery. The system uses a trained machine learning model to perform this classification. The system can accept input either as text or as voice recordings
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