Translation
Transformers
PyTorch
TensorFlow
Safetensors
English
Lithuanian
marian
text2text-generation
opus-mt-tc
Eval Results (legacy)
Instructions to use Helsinki-NLP/opus-mt-tc-big-en-lt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-tc-big-en-lt with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-lt")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tc-big-en-lt") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-tc-big-en-lt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| eng-lit flores101-dev 0.58441 26.5 997 20018 | |
| eng-lit flores101-devtest 0.59593 28.0 1012 20695 | |
| eng-lit newsdev2019 0.58444 26.6 2000 39627 | |
| eng-lit newstest2019 0.51559 17.5 998 19711 | |
| eng-lit tatoeba-test-v2020-07-28 0.67475 39.5 2500 14798 | |
| eng-lit tatoeba-test-v2021-03-30 0.67445 39.5 5003 29598 | |
| eng-lit tatoeba-test-v2021-08-07 0.67434 39.5 2528 14942 | |