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3db4bdd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | Quick Start
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First, load one of the BGE embedding model:
.. code:: python
from FlagEmbedding import FlagAutoModel
model = FlagAutoModel.from_finetuned('BAAI/bge-base-en-v1.5')
.. tip::
If there's difficulty connecting to Hugging Face, you can use the `HF mirror <https://hf-mirror.com/>`_ instead.
.. code:: bash
export HF_ENDPOINT=https://hf-mirror.com
Then, feed some sentences to the model and get their embeddings:
.. code:: python
sentences_1 = ["I love NLP", "I love machine learning"]
sentences_2 = ["I love BGE", "I love text retrieval"]
embeddings_1 = model.encode(sentences_1)
embeddings_2 = model.encode(sentences_2)
Once we get the embeddings, we can compute similarity by inner product:
.. code:: python
similarity = embeddings_1 @ embeddings_2.T
print(similarity)
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