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
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (3527fd4f41524b064cc486b234284d5b8515334c)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:561c41232a4719517645bba3d023b351564b6306233e124046a068a539370334
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size 711440320
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