Instructions to use Helsinki-NLP/opus-mt-en-ROMANCE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-ROMANCE 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-en-ROMANCE")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ROMANCE") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-ROMANCE", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#6 opened almost 2 years ago
by
SFconvertbot
Is there a limitation with the input token length with Helsinki-NLP/opus-mt-en-ROMANCE model ?
#5 opened almost 3 years ago
by
Arsh25
Adding `safetensors` variant of this model
#3 opened about 3 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#2 opened over 3 years ago
by
SFconvertbot