ToLD-Br
pytorch-sentiment-analysis
| ToLD-Br | pytorch-sentiment-analysis | |
|---|---|---|
| 1 | 2 | |
| 34 | 4,255 | |
| - | - | |
| 2.6 | 4.0 | |
| 2 months ago | about 2 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU General Public License v3.0 or later | MIT License |
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ToLD-Br
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Toxicity in Tweets using a BERT model
The dataset is based on ToLD-Br, which is a huge dataset of tweets (or is it Xeets now?) that contains some additional info such as a classification if the text contains homophobia, obscenity, insults, racism, misogyny and xenophobia. The dataset for the competition, however, is a simple toxicity column.
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
What are some alternatives?
spark-nlp - State of the Art Natural Language Processing
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.
Time-Series-Forecasting-Using-LSTM - Time-Series Forecasting on Stock Prices using LSTM
Behavior-Sequence-Transformer-Pytorch - This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf
malaya - Natural Language Toolkit for Malaysian language, https://malaya.readthedocs.io/
afinn - AFINN sentiment analysis in Python
n4m-sentiment - Sentiment Analysis for your MaxMSP patches - made easy.
MachineLearningWithPython - Get started with Machine Learning with Python - An introduction with Python programming examples
gpt-3-simple-tutorial - Generate SQL from Natural Language Sentences using OpenAI's GPT-3 Model
ecco - Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).
pytorch-seq2seq - Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
BERT-for-Mobile - Compares the DistilBERT and MobileBERT architectures for mobile deployments.