Instructions to use Helsinki-NLP/opus-mt-zlw-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-zlw-en 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-zlw-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-zlw-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-zlw-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b79a32beea6a0f026fccde1d83ec42a66457d2a14751cc6a938941d2ce50e6c
- Size of remote file:
- 298 MB
- SHA256:
- 25af4cf601a7d5e1bb80fe8d822abdfc0a9567c5c4979872aed303cdd4daf8fe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.