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Need Universal Sentence Encoder model for natural language embedding #19

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destroy314 opened this issue Aug 14, 2023 · 3 comments
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@destroy314
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The policy takes a 512-d natural_language_embedding as input. Can I just load it from TF Hub (https://tfhub.dev/google/universal-sentence-encoder/4) and embed my sentence, or would you please share the model checkpoint you have used?

@Asad-Shahid
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Hi, Did you find any workaround for this?

@ckennedy2050
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I've confirmed the USE encoder on TF Hub @ https://tfhub.dev/google/universal-sentence-encoder/4 does not generate the same natural_language_embedding as in the datasets used (https://docs.google.com/spreadsheets/d/1rPBD77tk60AEIGZrGSODwyyzs5FgCU9Uz3h-3_t2A9g/edit#gid=0). Can anyone share how to generate these embeddings for use with this project? Thank you!

@safsin
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safsin commented Feb 19, 2024

After checking the example for RT1-X, it uses the USE encoder (https://tfhub.dev/google/universal-sentence-encoder-large/5), which generates the same embeddings as that in RT1 dataset.

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