Instructions to use Helsinki-NLP/opus-mt-af-eo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-af-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-af-eo")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-af-eo") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-af-eo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Helsinki-NLP/opus-mt-af-eo: direct link, hf CLI and curl.
- Browser
- Download file 194 MB
-
https://huggingface.co/Helsinki-NLP/opus-mt-af-eo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Helsinki-NLP/opus-mt-af-eo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Helsinki-NLP/opus-mt-af-eo/resolve/main/pytorch_model.bin
194 MB
- Xet hash:
- 9667ecbc3936f7857dfd38208ef294324424cda8bdeab598c7ce22ca165e10a5
- Size of remote file:
- 194 MB
- SHA256:
- 2f111bcec319271bb7d3cbce897c66e77e945ed6cdcb2410e3ebf817b300fcab
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