Instructions to use Helsinki-NLP/opus-mt-en-sn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-sn 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-sn")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-sn") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-sn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c49fc87fbf5b9cde4baaeb4c6f36d20cf49fa5fa66abfeb13c2ecb9d06808a29
- Size of remote file:
- 304 MB
- SHA256:
- e1b1f534e21c0a2a8cb25416b35a91280bb195c3de599bad026f80697edb2eba
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.