Instructions to use Helsinki-NLP/opus-mt-es-tw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-tw 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-es-tw")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-tw") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-tw", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3b46ed06484e7e3f3acebee5e3e00a2e103e8b1489c60875844734b570c6cae
- Size of remote file:
- 302 MB
- SHA256:
- e4ba314c50ad1570ee787f035374fc98922c8cf4b0df37ff7642ecfde8dce494
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