ToLD-Br
Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysis (by JAugusto97)
| ToLD-Br | toldbr-bert-text-classification-pt-br | |
|---|---|---|
| 1 | 1 | |
| 34 | 0 | |
| - | - | |
| 2.6 | 4.7 | |
| 2 months ago | about 1 month ago | |
| Jupyter Notebook | Python | |
| GNU General Public License v3.0 or later | - |
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.
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.
ToLD-Br
Posts with mentions or reviews of ToLD-Br.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-11.
-
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.
toldbr-bert-text-classification-pt-br
Posts with mentions or reviews of toldbr-bert-text-classification-pt-br.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-11.
-
Toxicity in Tweets using a BERT model
And that's it! If you want to check it out and train/test this model yourself, feel free to check the code in my GitHub repository!