Quickstart
Get started with CTranslate2 with end-to-end examples using machine translation models.
See also
The Transformers guide which contains a bunch of examples for various models.
Python
Start using CTranslate2 from Python by converting a pretrained model and running your first translation.
1. Install the Python packages
pip install ctranslate2 OpenNMT-py==2.* sentencepiece
2. Download the English-German Transformer model trained with OpenNMT-py
wget https://s3.amazonaws.com/opennmt-models/transformer-ende-wmt-pyOnmt.tar.gz
tar xf transformer-ende-wmt-pyOnmt.tar.gz
3. Convert the model to the CTranslate2 format
ct2-opennmt-py-converter --model_path averaged-10-epoch.pt --output_dir ende_ctranslate2
4. Translate texts with the Python API
import ctranslate2
import sentencepiece as spm
translator = ctranslate2.Translator("ende_ctranslate2/", device="cpu")
sp = spm.SentencePieceProcessor("sentencepiece.model")
input_text = "Hello world!"
input_tokens = sp.encode(input_text, out_type=str)
results = translator.translate_batch([input_tokens])
output_tokens = results[0].hypotheses[0]
output_text = sp.decode(output_tokens)
print(output_text)
This code should print the sentence:
Hallo Welt!
If that’s the case, you successfully converted and executed a translation model with CTranslate2! Consider browsing the other sections for more information and examples.
C++
Start using the CTranslate2 library in your own C++ project.
1. Compile and Install CTranslate2
mkdir build && cd build
cmake ..
make -j4 install
It is important that the library is getting installed into a directory that is on the CMAKE_PREFIX_PATH
, otherwise you can install to a custom directory, e.g.:
export CTRANSLATE_INSTALL_PATH=$(pwd)/install
cmake .. -DCMAKE_INSTALL_PREFIX=$CTRANSLATE_INSTALL_PATH
make -j4 install
See the installation guide for more information.
2. Add CTranslate2 to your CMakeLists.txt
cmake_minimum_required (VERSION 2.8.11)
project (CTRANSLATE2_DEMO)
find_package(ctranslate2)
add_executable (main main.cpp)
target_link_libraries(main CTranslate2::ctranslate2)
3. Have a model ready in the CTranslate2 format
ct2-transformers-converter --model Helsinki-NLP/opus-mt-en-de --output_dir opus-mt-en-de
4. Write the translation C++ code using the API
You will need to have your input string tokenised, which depends on what type of model you are using. Have a look at the guides to get tokens from your input string.
#include <iostream>
#include <vector>
#include "ctranslate2/translator.h"
int main(int argc, char* argv[]) {
const std::string model_path("opus-mt-en-de");
const ctranslate2::models::ModelLoader model_loader(model_path);
ctranslate2::Translator translator(model_loader);
const std::vector<std::vector<std::string>> batch = {{"▁Hello", "▁World", "!", "</s>"}};
const auto translation = translator.translate_batch(batch);
for (const auto& token : translation[0].output())
std::cout << token << ' ';
std::cout << std::endl;
}
5. Compile and run the example
cmake .
make
./main
If you have installed the CTranslate library to a custom path use:
cmake -DCMAKE_PREFIX_PATH=$CTRANSLATE_INSTALL_PATH .
This code should print the output tokens:
▁Hall o ▁Welt !
If that’s the case, you successfully converted and executed a translation model with CTranslate2!
Important
(De)tokenisation is handled outside of CTranslate2, so make sure to properly tokenise the input and detokenise the output.