Instructions to use Helsinki-NLP/opus-mt-en-alv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-alv 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-alv")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-alv") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-alv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b37f156d09540a23d51086dd19d783eb703d9786819ad311c5532e095427640
- Size of remote file:
- 305 MB
- SHA256:
- 5c94b2423bdabcd2f81d1e757f53b95942ae446d66cc15f221ae6b6188da92d7
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