Instructions to use Helsinki-NLP/opus-mt-es-gl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-gl 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-gl")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-gl") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-gl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8c701910ba0640eb53a65c7a014b43cef4c21674699720b126d1c0fd983834d
- Size of remote file:
- 191 MB
- SHA256:
- e895f02afd79b0ff66fcfa40f3a21875b8d64fb5eb883e016d9a7617b1cf27a7
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