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--- |
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library_name: model2vec |
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license: mit |
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model_name: cnmoro/low-dimension-static-model |
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tags: |
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- embeddings |
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- static-embeddings |
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- sentence-transformers |
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--- |
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A low dimension static embedding model (3d) to be used as a text encoder in ML pipelines |
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## Installation |
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Install model2vec using pip: |
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``` |
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pip install model2vec |
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``` |
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```python |
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from sentence_transformers import SentenceTransformer |
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# Load a pretrained Sentence Transformer model |
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model = SentenceTransformer("cnmoro/low-dimension-static-model") |
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# Compute text embeddings |
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embeddings = model.encode(["Example sentence"]) |
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``` |
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