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Extract Probabilities from the BERT model (NLP), GitHub Repo Available

I need to extract document probabilities from the BERT model. There are many posts talking about implementation. The Github Repo provides docker, so install the repo should not be a problem.

For quick starts, this might be helpful:

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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

Compétences : Python, Exploitation de Données, Deep Learning

Concernant l'employeur :
( 0 commentaires ) Central, Hong Kong

Nº du projet : #21279001

Décerné à:


Hello, I have worked with BERT before and I can do your tasks within budget and timeline.

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5 freelance font une offre moyenne de $158 pour ce travail


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Hi, there. I am very interested in your Python project. I have high Python skill and can work anytime from now on. Please contact me and discuss further. Thanks.

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