Streamlit Machine Translate

Streamlit Machine Translate

Translates text between languages in a browser page, with a choice of several open machine translation models. Suits anyone who needs a quick translation, or a Streamlit app to read and adapt.

Made by TiberiuCristianLeon on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.

About

What it is: This Space is a small Streamlit app that translates text with machine translation models. It names several of them, among them Lego-MT and a set of Helsinki-NLP opus-mt models. You use it in a browser, with nothing to install.

Who it suits: People who need a quick translation of a short text, and developers who want a working Streamlit translator to read and adapt.

Industry | Who uses it | How they use it | Example
Education | Language learners | Check what a short passage means | Translating a sentence from a lesson text
Software | Developers | Read and adapt a small Streamlit translation app | Reading app.py and translator.py to see how the app is put together
Research | NLP hobbyists | Try different open translation models on the same text | Running one sentence through two of the named models

You can skip it if you need whole documents translated, because the source mentions no file handling.

Where to use it:

• A web browser, on the Space's own page at Hugging Face
• Windows, macOS or Linux with Python, as a copy on your own computer

Use case | Who | What they get back
Quick translation | Anyone reading foreign text | The text in the language they pick
Model trial | Developers and hobbyists | The output of the model they chose

How to set it up:

• A browser, if you only use the Space online
• Python and pip, if you run a copy yourself

1. Open the Space's page on Hugging Face to use it online. Nothing needs installing.
2. For a local copy, install the huggingface_hub package and download the Space's files.
3. Move into the new folder, then install Streamlit and the Python packages in requirements.txt.
4. Start the app with streamlit run.

pip install -U huggingface_hub
hf download TiberiuCristianLeon/StreamlitTranslate --repo-type space --local-dir StreamlitTranslate
cd StreamlitTranslate
pip install streamlit==1.61.1
pip install -r requirements.txt

How to use it: Open the page, type or paste your text, pick the languages and the model the page offers, and read the translation it shows. On your own computer, start the app first and open the address Streamlit prints.

streamlit run app.py

Tool | What it does
streamlit run app.py | Starts the translator on your own computer

Example: You paste a short English sentence, choose German and one of the listed models, and the page shows the German sentence below it.

For newcomers and experts: If you are new to this, open the Space and translate one short sentence. Then change the model and see how the wording shifts.

Under the hood, the repository holds app.py, translator.py, languagecodes.py, a tokenizer file and a table of language codes. The models are Lego-MT and several Helsinki-NLP opus-mt Bible models, some covering many languages at once. The Space runs on Hugging Face's basic CPU hardware, so a copy on your own machine suits heavier use.

Open the Space or run a copy
Type your text
Pick languages and a model
The app runs the chosen model
The translation shows on the page

Good to know:

• Built with Streamlit 1.61.1, and the main file is app.py
• License: gpl-3
• Cost to run: none named
• Data it reaches: none named

On Hugging Face, 13 November 2026

• Likes: 16
• Built with: streamlit
• License: gpl-3.0

Links

• Space: https://huggingface.co/spaces/TiberiuCristianLeon/StreamlitTranslate
• Files: https://huggingface.co/spaces/TiberiuCristianLeon/StreamlitTranslate/tree/main

Try it

Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.