Instructions to use Helsinki-NLP/opus-mt-en-eo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-eo 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-en-eo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-eo") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-eo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-en-eo: direct link, hf CLI and curl.
- Browser
- Download file 300 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-en-eo/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-en-eo@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-en-eo/resolve/refs%2Fpr%2F2/pytorch_model.bin
300 MB
- Xet hash:
- 72b28e9f5c8f6a32e957e635ed547fe9c64f6d17465ad3ce78aa95a9b0053534
- Size of remote file:
- 300 MB
- SHA256:
- 333fabb9de15298cda12bdd5d36698f7f5d190ddb0aa2ef5617f1611268c98de
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