Instructions to use falkne/bert-europarl-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use falkne/bert-europarl-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="falkne/bert-europarl-en")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("falkne/bert-europarl-en") model = AutoModel.from_pretrained("falkne/bert-europarl-en") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
Bert Europarl (bert-europarl-en)
This model is a fine-tuned version of the BERT base model. It was introduced in this paper.
Model description
The BERT base language model was fine-tuned on an English portion of the Europarl corpus. The model was trained on 1,076,468 sentences of the Europarl corpus. The sentences were sampled from the English portion of Europarl.
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