Hi Kathrin,
Thanks for your valuable feedback.
Additionally, I checked (many) nodes to see if I can add a sentence context to the embedding. Couldn’t find any.
But if there’s a node in Knime where I can load vectors of a pre-trained model’s sentence embedding, it would be great.
Say, for eg: below are the columns (separated by ‘|’ ) of that sentence-embedded csv file (not displayed well. it has 2 rows, for 2 sentences).
Sentences | Embeddings
"come back" | "tf.Tensor([ 3.95798124e-03 9.25457552e-02 9.64313466e-03 -2.79159304e-02 -5.22264242e-02 4.17356715e-02 -1.33834435e-02 4.40481585e-03 ], shape=(8,), dtype=float32)"
"move aside" | "tf.Tensor([ 3.95798124e-03 9.25457552e-02 9.64313466e-03 -2.79159304e-02 -5.22264242e-02 4.17356715e-02 -1.33834435e-02 4.40481585e-03 ], shape=(8,), dtype=float32)"
I was thinking if i can load this file in Knime to then calculate cosine similarity etc. It would be really helpful if this can be done.
[Sorry if this pertains to a separate question, please let me know, I can repost it separately]