Sentence Similarity
Transformers
PyTorch
Safetensors
English
bert
feature-extraction
text-embeddings-inference
Instructions to use SAP/miCSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SAP/miCSE with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SAP/miCSE") model = AutoModel.from_pretrained("SAP/miCSE") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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# **m**utual **i**nformation **C**ontrastive **S**entence **E**mbedding (**miCSE**) for Low-shot Sentence Embeddings
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Paper accepted at [ACL 2023](https://2023.aclweb.org/)
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# Brief Model Description
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license: apache-2.0
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# **m**utual **i**nformation **C**ontrastive **S**entence **E**mbedding (**miCSE**) for Low-shot Sentence Embeddings
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Paper accepted at [ACL 2023](https://2023.aclweb.org/)[](https://arxiv.org/abs/2211.04928)[](https://github.com/SAP-samples/acl2023-micse/)
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# Brief Model Description
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