ToLD-Br Alternatives

Similar projects and alternatives to ToLD-Br based on common topics and language

toldbr-bert-text-classification-pt-br

1 0 4.7 Python ToLD-Br VS toldbr-bert-text-classification-pt-br
mgpt

1 194 3.1 Jupyter Notebook ToLD-Br VS mgpt

Multilingual Generative Pretrained Model
WorkOS

workos.com featured

The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
Puffin-Discord-Bot

1 7 8.2 Jupyter Notebook ToLD-Br VS Puffin-Discord-Bot

Open source discord moderation bot leveraging NLP with a focus on explainability.
FLAML

9 3,679 7.9 Jupyter Notebook ToLD-Br VS FLAML

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
nlp-tutorial

1 13,691 0.0 Jupyter Notebook ToLD-Br VS nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers
pytorch-sentiment-analysis

2 4,225 4.0 Jupyter Notebook ToLD-Br VS pytorch-sentiment-analysis

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
adapters

4 2,390 8.6 Jupyter Notebook ToLD-Br VS adapters

A Unified Library for Parameter-Efficient and Modular Transfer Learning
InfluxDB

www.influxdata.com featured

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better ToLD-Br alternative or higher similarity.

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ToLD-Br reviews and mentions

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
2 projects | dev.to | 11 Apr 2024

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.