NL_Parser_using_Spacy VS bert-sklearn

Compare NL_Parser_using_Spacy vs bert-sklearn and see what are their differences.

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NL_Parser_using_Spacy bert-sklearn
1 1
22 293
- -
0.0 0.0
over 1 year ago over 1 year ago
Jupyter Notebook Jupyter Notebook
- Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

NL_Parser_using_Spacy

Posts with mentions or reviews of NL_Parser_using_Spacy. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-01.

bert-sklearn

Posts with mentions or reviews of bert-sklearn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-08.

What are some alternatives?

When comparing NL_Parser_using_Spacy and bert-sklearn you can also consider the following projects:

bert - TensorFlow code and pre-trained models for BERT

txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

OpenAI-CLIP - Simple implementation of OpenAI CLIP model in PyTorch.

kruk - Ukrainian instruction-tuned language models and datasets

NLU-engine-prototype-benchmarks - Demo and benchmarks for building an NLU engine similar to those in voice assistants. Several intent classifiers are implemented and benchmarked. Conditional Random Fields (CRFs) are used for entity extraction.

fake-news - Building a fake news detector from initial ideation to model deployment

ABSA_Project_4 - This project takes advantange of the parsing and part of speech tagging capabilites of Spacy's pipeline in order to extract aspect/opinion/sentiment triplets. Cluster aspects using unsupervised learning to process sentiment for large amazon review datasets.

tf-transformers - State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).

TabularSemanticParsing - Translating natural language questions to a structured query language

German-NER-BERT - German NER on Legal Data using BERT

pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.