Instructions to use malinali-app/opus-mt-ee-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malinali-app/opus-mt-ee-de 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="malinali-app/opus-mt-ee-de")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("malinali-app/opus-mt-ee-de") model = AutoModelForSeq2SeqLM.from_pretrained("malinali-app/opus-mt-ee-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer-dec.json from malinali-app/opus-mt-ee-de: direct link, hf CLI and curl.
- Browser
- Download file 4.24 MB
-
https://huggingface.co/malinali-app/opus-mt-ee-de/resolve/main/tokenizer-dec.json
- Command line
-
hf download hf://malinali-app/opus-mt-ee-de/tokenizer-dec.json
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curl -L -o tokenizer-dec.json https://huggingface.co/malinali-app/opus-mt-ee-de/resolve/main/tokenizer-dec.json
4.24 MB
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