pytorch-sentiment-analysis
malaya
| pytorch-sentiment-analysis | malaya | |
|---|---|---|
| 2 | 1 | |
| 4,225 | 456 | |
| - | 1.1% | |
| 4.0 | 9.0 | |
| about 1 month ago | 5 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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pytorch-sentiment-analysis
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Ich habe einen Bot gebastelt für Ovalwichs
z.B. https://github.com/bentrevett/pytorch-sentiment-analysis
- German language sentiment classification - NLP Deep Learning
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.
What are some alternatives?
spark-nlp - State of the Art Natural Language Processing
afinn - AFINN sentiment analysis in Python
Basic-UI-for-GPT-J-6B-with-low-vram - A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.
tf-transformers - State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).
Time-Series-Forecasting-Using-LSTM - Time-Series Forecasting on Stock Prices using LSTM
wink-nlp - Developer friendly Natural Language Processing ✨
Behavior-Sequence-Transformer-Pytorch - This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf
wink-eng-lite-model - English lite language model for wink-nlp.
German-NER-BERT - German NER on Legal Data using BERT
n4m-sentiment - Sentiment Analysis for your MaxMSP patches - made easy.
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 !