malaya
German-NER-BERT
| malaya | German-NER-BERT | |
|---|---|---|
| 1 | 2 | |
| 457 | 7 | |
| 1.3% | - | |
| 9.0 | 0.0 | |
| 7 days ago | almost 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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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.
malaya
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Public Sentiment regarding COVID19 from Malay Tweets vs Daily Case Numbers of Malaysia
Hey guys! I've been doing some web scraping on Malay tweets regarding COVID19. I decided to do some sentiment analysis using a NLP model (model is publicly available at https://github.com/huseinzol05/malaya). What the model does is taking in a chunk of text and outputs a sentiment score between 0 to 1 (1 being the text has 100% positive sentiment and 0 being the text is 100% negative). The model is not 100% accurate but it is considered to be comparable to other state-of-the-art models.
German-NER-BERT
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[P] German NER on Legal Data using BERT
Link to project: https://github.com/harshildarji/German-NER-BERT/
What are some alternatives?
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
bert-sklearn - a sklearn wrapper for Google's BERT model
afinn - AFINN sentiment analysis in Python
docutron - Docutron Toolkit: detection and segmentation analysis for legal data extraction over documents.
tf-transformers - State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).
wink-nlp - Developer friendly Natural Language Processing ✨
wink-eng-lite-model - English lite language model for wink-nlp.
nlphose - Enables creation of complex NLP pipelines in seconds, for processing static files or streaming text, using a set of simple command line tools. Perform multiple operation on text like NER, Sentiment Analysis, Chunking, Language Identification, Q&A, 0-shot Classification and more by executing a single command in the terminal. Can be used as a low code or no code Natural Language Processing solution. Also works with Kubernetes and PySpark !
face-emotion-recognition - Efficient face emotion recognition in photos and videos
Twitter-sentiment-analysis - A sentiment analysis model trained with Kaggle GPU on 1.6M examples, used to make inferences on 220k tweets about Messi and draw insights from their results.
umibench - Testbench for sentiment and factuality in texts.