Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
nlp
multimodal
beit
beit-3
deepnet
document-ai
foundation-models
kosmos
kosmos-1
layoutlm
layoutxlm
llm
minilm
mllm
pre-trained-model
textdiffuser
trocr
unilm
xlm-e
Обновлено 2024-11-09 13:45:59 +03:00
This package features data-science related tasks for developing new recognizers for Presidio. It is used for the evaluation of the entire system, as well as for evaluating specific PII recognizers or PII detection models.
machine-learning
deep-learning
nlp
natural-language-processing
privacy
ner
transformers
pii
named-entity-recognition
spacy
flair
Обновлено 2024-10-27 15:51:02 +03:00
Scripts to parse arxiv documents for NLP tasks
Обновлено 2023-06-12 22:03:00 +03:00
Automatically extracting keyphrases that are salient to the document meanings is an essential step to semantic document understanding. An effective keyphrase extraction (KPE) system can benefit a wide range of natural language processing and information retrieval tasks. Recent neural methods formulate the task as a document-to-keyphrase sequence-to-sequence task. These seq2seq learning models have shown promising results compared to previous KPE systems The recent progress in neural KPE is mostly observed in documents originating from the scientific domain. In real-world scenarios, most potential applications of KPE deal with diverse documents originating from sparse sources. These documents are unlikely to include the structure, prose and be as well written as scientific papers. They often include a much diverse document structure and reside in various domains whose contents target much wider audiences than scientists. To encourage the research community to develop a powerful neural model with key phrase extraction on open domains we have created OpenKP: a dataset of over 150,000 documents with the most relevant keyphrases generated by expert annotation.
Обновлено 2023-06-12 21:21:58 +03:00
Various tasks for CI Automation team
Обновлено 2022-12-08 13:02:06 +03:00
An efficient implementation of the popular sequence models for text generation, summarization, and translation tasks. https://arxiv.org/pdf/2106.04718.pdf
Обновлено 2022-08-17 19:38:06 +03:00
Unsupervised Domain Adaptation for Computer Vision Tasks
Обновлено 2022-04-21 12:34:36 +03:00
INACTIVE - http://mzl.la/ghe-archive - Runner is a project that manages starting tasks in a defined order. If tasks fail, the chain can be retried, or halted.
Обновлено 2015-10-29 00:13:56 +03:00