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:
- b2a045e6a9f098f89af386cad251406cf9a3f521af2fe7e87f4920b2e4c26c58
- Size of remote file:
- 711 MB
- SHA256:
- 561c41232a4719517645bba3d023b351564b6306233e124046a068a539370334
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