Instructions to use Helsinki-NLP/opus-mt-fi-sq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-fi-sq 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-sq")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fi-sq") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-fi-sq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cf7e84c63abe9e0fadd0f9b2bda761ad19247bf857add8ca0e5a387cbb37334
- Size of remote file:
- 303 MB
- SHA256:
- 5c269d88aed0e369f2863c000030c434975b2c2cb36f3c598c54d6cde6f6090a
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