wehub-resource-sync
27 lines
757 B
Python
27 lines
757 B
Python
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""" OpenVINO embedding models - this example shows how to use OpenVINO embedding
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models which can be prepared in batch, and used in conjunction with vector databases
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or other vector semantic search retrieval applications.
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Prerequisites:
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-- pip3 install openvino
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"""
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from llmware.models import ModelCatalog
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# industry-bert-contracts-ov
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# industry-bert-insurance-ov
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# all-mini-lm-l6-v2-ov
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# all-mpnet-base-v2-ov
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model = ModelCatalog().load_model("industry-bert-contracts-ov")
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text = "We are at the airport waiting for our flight."
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text2 = "The airport is boring, but OK to work from."
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text3 = "I am looking forward to our trip."
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embedding = model.embedding([text, text2,text3])
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print("--test: embedding - ", embedding.shape, embedding)
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