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Private Cybersecurity NER BERT-base-cased model
This method includes a Python script and files of a BERT-base-cased model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that... -
Cybersecurity NER RoBERTa-base model
This method includes a Python script and files of a RoBERTa-base model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that will...-
JSON
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TXT
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BIN
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JSON
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ZIP
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JSON
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JSON
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ZIP
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JSON
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ZIP
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py
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JSON
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Cybersecurity NER SecureBERT model
This method includes a Python script and files of a SecureBERT model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that will be...-
JSON
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TXT
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BIN
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JSON
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ZIP
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ZIP
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JSON
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JSON
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JSON
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ZIP
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TXT
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text/x-python
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JSON
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Private Cybersecurity NER dataset
Our dataset is created by merging APTNER and CyNER datasets, containing 13601 sentences, 347779 tokens, and 37684 entities. The split ratio was roughly 70% for training and... -
SWH Filenames
A 69 GB dataset with ~2.3 billion strings representing deduplicated names of source code files collected by Software Heritage, the great library of source code...-
ZIP
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ZIP
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Private Smart Cities Weather and Pollution conditions
A set of weather and climatic conditions gathered during the Toolsmart PoN project ( Open Community PA 2020 – Pon Governance 2014-2020). Data are obtained from IoT based... -
Santorini Tweets July-August 2021
This dataset contains 225.501 tweets written by 141.277 users. These tweets are geolocated in Santorini, or they contain the word or the hashtag "santorini" in the text. They...-
ZIP
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ZIP
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SMAPH Query Entity Linker
The SMAPH system links queries to the entities it mentions, disambiguating mentions if needed. Entities are Wikipedia pages. This problem is known as "entity recognition and...-
HTML
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HTML
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Quantum Distance-Based Classifier
The Quantum Distance-Based Classifier is a technique inspired by the classical k-Nearest Neighbors that leverages quantum properties to perform prediction. -
Wikipedia Word Embeddings
Embeddings were created through applying word2vec skipgram to a corpus of wikipedia non-stub articles from a December 2015 English dump with the following parameters: -cbow 0...
