Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
nlp
machine-learning
text-classification
named-entity-recognition
seq2seq
transfer-learning
ner
bert
sequence-labeling
nlp-framework
bert-model
text-labeling
gpt-2
-
Updated
Jul 9, 2021 - Python
Add a way to change the sample id output in the annotation process to a specific number (see picture).
Reason: I want to annotate large text and the app don't like it when the documents to annotate are too large, so I spitted in a sentence the document but I would like to be able to