Instructions to use sshleifer/opus-mt-en-he with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/opus-mt-en-he 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="sshleifer/opus-mt-en-he")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/opus-mt-en-he") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/opus-mt-en-he") - Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:548799558c0bf08faae35eb8b5484e4c9bd13654f52062494f3fdf286ae4818f
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