argilla VS small-text

Compare argilla vs small-text and see what are their differences.

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argilla small-text
15 4
3,122 520
2.3% 0.4%
9.8 7.6
5 days ago 3 days ago
Python Python
Apache License 2.0 MIT License
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.

argilla

Posts with mentions or reviews of argilla. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-05.

small-text

Posts with mentions or reviews of small-text. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-06.

What are some alternatives?

When comparing argilla and small-text you can also consider the following projects:

snorkel - A system for quickly generating training data with weak supervision

transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format

happy-transformer - Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.

doccano - Open source annotation tool for machine learning practitioners.

NewsMTSC - Target-dependent sentiment classification in news articles reporting on political events. Includes a high-quality data set of over 11k sentences and a state-of-the-art classification model.

cleanlab - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

automl-docker - CLI-based tool to automatically build ML models from training data into a servable Docker container

data-centric-ai - Resources for Data Centric AI

DECIMER-Image_Transformer - DECIMER: Deep Learning for Chemical Image Recognition using Efficient-Net V2 + Transformer

trankit - Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing

MONAILabel - MONAI Label is an intelligent open source image labeling and learning tool.