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This repository has been archived by the owner on Oct 31, 2023. It is now read-only.
how is the column embedding and the context embedding value changing every time we run encode(with pre-trained model) if we are running on the same table with the same context? (We tried with just one row in the table, and the embedding changes every time)
For example:
For the same table and same context, we get the following two embeddings.
For example:
For the same table and same context, we get the following two embeddings.
tensor([-6.5471e-02, -1.1527e-01, 5.5206e-01, -3.9907e-02, 4.8929e-01,
3.5280e-01, 1.8725e-01, 8.9385e-01, -1.9507e-01, 2.4612e-01,
tensor([-1.6841e-01, -2.1637e-02, 5.4372e-01, -1.2783e-02, 2.2790e-01,
8.3290e-02, 4.2798e-01, 7.9061e-01, -3.3040e-01, 3.3663e-01,
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