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It would be great if we could revise our current approach with the election 2020 data, to use whichever model has been set as the MODEL_ID.
This means we need to operationalize the migration queries through the bq service instead of running them manually / via README. We will need to construct the queries according to which model has been set as the MODEL_ID.
We can use a dictionary mapping of model id's to corresponding table names. Let's use different tables for the different models, because some models embeddings have more than others, and there aren't that many models.
The text was updated successfully, but these errors were encountered:
For next steps in research, we would like to fetch embeddings using openai's two new models, the
text-embedding-3-small
andtext-embedding-3-large
It would be great if we could revise our current approach with the election 2020 data, to use whichever model has been set as the
MODEL_ID
.This means we need to operationalize the migration queries through the bq service instead of running them manually / via README. We will need to construct the queries according to which model has been set as the
MODEL_ID
.We can use a dictionary mapping of model id's to corresponding table names. Let's use different tables for the different models, because some models embeddings have more than others, and there aren't that many models.
The text was updated successfully, but these errors were encountered: