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Extract Probabilities from the Skip-Thought model (NLP), GitHub Repo Available

I need to extract document probabilities from the Skip-Thought model. There are many posts talking about implementation. The Github Repo is read to use:

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I have 2 types of input files for two types of speeches (L and Q): one contains sentence_ID and content (T1_Table). The other has 2 columns, each line records the beginning and end of a paragraph: The beginning sentence_ID (starting from 0), end sentence_ID. Please note that the sentence IDs start from 0 (T2_Table).

We need to extract the probability of each paragraph for both two types of speech (L and Q) and save the embeddings for each sentence for both L and Q.

All files can be found here

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Final deliverables:

1. script

2. sentence embeddings with sentence_id for L and Q

3. paragraph probabilities with paragraph_id

Evner: Python, Datasøgning, Deep Learning

Om arbejdsgiveren:
( 0 bedømmelser ) Central, Hong Kong

Projekt ID: #21287670

Tildelt til:

dungforever

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