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README.md
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model = SentenceTransformer('thenlper/gte-base')
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embeddings = model.encode(sentences)
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print(cos_sim(embeddings[0], embeddings[1]))
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### Limitation
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If you find our paper or models helpful, please consider citing them as follows:
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-
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```
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@misc{li2023general,
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title={Towards General Text Embeddings with Multi-stage Contrastive Learning},
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model = SentenceTransformer('thenlper/gte-base')
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embeddings = model.encode(sentences)
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print(cos_sim(embeddings[0], embeddings[1]))
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```
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### Limitation
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If you find our paper or models helpful, please consider citing them as follows:
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```
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@misc{li2023general,
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title={Towards General Text Embeddings with Multi-stage Contrastive Learning},
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