Translation
Transformers
PyTorch
TensorFlow
Seselwa Creole French
Finnish
marian
text2text-generation
Instructions to use Helsinki-NLP/opus-mt-crs-fi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-crs-fi 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-crs-fi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-crs-fi") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-crs-fi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81aa8b596fd357016f6de962fbeb5e606c180f2ea7dd041e192349a17d8a8b4b
- Size of remote file:
- 278 MB
- SHA256:
- 0f3ae09e06e422864e30090290bd8b9aab09c80a92424d1f01f5dfa6dc27a62b
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