Instructions to use Helsinki-NLP/opus-mt-kg-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-kg-es 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-kg-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-kg-es") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-kg-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6988bcc15a1f3e9a4198f8ecf1b2a6924d393989be7ad143d704a5259062374
- Size of remote file:
- 281 MB
- SHA256:
- 1b55c0a18e399a5809069fdaa3aa57830fc4bd421ac15d15b15a1b7182c3f291
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