Instructions to use Helsinki-NLP/opus-mt-es-bcl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-bcl 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-bcl")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-bcl") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-bcl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b9c601abecd184432ae90a1e5d0e60bfe62b36aac27d5720c783fdeceaeedf9
- Size of remote file:
- 301 MB
- SHA256:
- b63b80c95b02220a51260155741d8f20a3cb93cce7e60348419f7a70391bc549
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