Instructions to use s-nlp/m3m_bert_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use s-nlp/m3m_bert_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="s-nlp/m3m_bert_encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("s-nlp/m3m_bert_encoder") model = AutoModel.from_pretrained("s-nlp/m3m_bert_encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92503b528ab8177048d9b3602f6a45fca77173e6981805a57403e94c3027c302
- Size of remote file:
- 711 MB
- SHA256:
- ff6a9023201cd3325c4f0696e487f533e7bc432c9a08a0928eb5b686d63c7c51
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