Instructions to use BenguerineMohammed/nmt-seq2seq-translator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenguerineMohammed/nmt-seq2seq-translator with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("BenguerineMohammed/nmt-seq2seq-translator") model = AutoModelForSeq2SeqLM.from_pretrained("BenguerineMohammed/nmt-seq2seq-translator") - Notebooks
- Google Colab
- Kaggle
| """ | |
| Public API of the NMT package. | |
| Usage: | |
| from src import translate_text, calculate_bleu | |
| from src import SUPPORTED_LANGUAGES | |
| """ | |
| from .languages import LANGUAGE_CODES, SUPPORTED_LANGUAGES, get_flores_code, get_speech_code | |
| from .translate import translate_text, batch_translate | |
| from .speech import speech_to_text | |
| from .evaluate import calculate_bleu, corpus_bleu | |
| __all__ = [ | |
| "LANGUAGE_CODES", | |
| "SUPPORTED_LANGUAGES", | |
| "get_flores_code", | |
| "get_speech_code", | |
| "translate_text", | |
| "batch_translate", | |
| "speech_to_text", | |
| "calculate_bleu", | |
| "corpus_bleu", | |
| ] | |