I can not get expected result following the quick start demo
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Description
I did it as link https://opennmt.net/CTranslate2/quickstart.html
c++ code as below:
`int main()
{
//system("chcp 850");
const std::string model_path("D:\\code\\CTranslate2\\models\\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;
return 0;
}`
but the output is:
鈻? 鈻丯ein , 鈻乶ein .
instead of '▁Hall o ▁Welt !' that in document.
my model is generated from following command:
huggingface-cli download --resume-download --local-dir-use-symlinks False Helsinki-NLP/opus-mt-en-de
cd D:\code\CTranslate2\models
ct2-transformers-converter --model Helsinki-NLP/opus-mt-en-de --quantization int8 --output_dir opus-mt-en-de
I need help.
sorry for my poor English.
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
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Research direction
Start with the C++ quick-start snippet and the Hugging Face download and ct2-transformers-converter commands shown in the issue. Compare the generated model's translation output with the quick-start expectation, including the displayed token encoding. Done means the same model and C++ example produce the documented output or the cause of the discrepancy is documented.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100