Instructions to use Helsinki-NLP/opus-mt-fi-mos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-fi-mos 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-fi-mos")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fi-mos") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-fi-mos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97d1b5ee2e828514dfad06163cb298612e4937a7abdcc71abe6e7ab9c0126bd4
- Size of remote file:
- 282 MB
- SHA256:
- fcbd743ceca1606367f56a700e8fd72d97c69dc2c2a8e34e5a02a4fd7cee7785
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