malaya VS pytorch-sentiment-analysis

Compare malaya vs pytorch-sentiment-analysis and see what are their differences.

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malaya pytorch-sentiment-analysis
1 2
457 4,247
1.3% -
9.0 4.0
8 days ago about 2 months ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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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

Posts with mentions or reviews of malaya. We have used some of these posts to build our list of alternatives and similar projects.
  • Public Sentiment regarding COVID19 from Malay Tweets vs Daily Case Numbers of Malaysia
    1 project | /r/malaysia | 19 Sep 2021
    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.

pytorch-sentiment-analysis

Posts with mentions or reviews of pytorch-sentiment-analysis. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing malaya and pytorch-sentiment-analysis you can also consider the following projects:

afinn - AFINN sentiment analysis in Python

spark-nlp - State of the Art Natural Language Processing

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

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.

wink-nlp - Developer friendly Natural Language Processing ✨

Time-Series-Forecasting-Using-LSTM - Time-Series Forecasting on Stock Prices using LSTM

wink-eng-lite-model - English lite language model for wink-nlp.

Behavior-Sequence-Transformer-Pytorch - This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf

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

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 !

n4m-sentiment - Sentiment Analysis for your MaxMSP patches - made easy.