Instructions to use Helsinki-NLP/opus-mt-da-fi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-da-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-da-fi")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-da-fi") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-da-fi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-da-fi: direct link, hf CLI and curl.
- Browser
- Download file 301 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-da-fi/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-da-fi/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-da-fi/resolve/main/pytorch_model.bin
301 MB
- Xet hash:
- 9881dcda36e024589156cbbbcf3a841e007dcdb8c26e59e785927f66c535ba96
- Size of remote file:
- 301 MB
- SHA256:
- 451d26069f7144adaf926d5debfe9f57a58870ff898f054cf6a8fc73133cef54
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