small-text
argilla
| small-text | argilla | |
|---|---|---|
| 4 | 15 | |
| 520 | 3,122 | |
| 0.4% | 2.3% | |
| 7.6 | 9.8 | |
| 5 days ago | 7 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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.
small-text
- Small-Text: Looking for Contributors (Active Learning, Text Classification, NLP)
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🤗 Active learning from scratch | Using Hugging Face Transformers, Rubrix, and small-text
If you are new to small-text: https://github.com/webis-de/small-text
- [P] Small-Text: Active Learning for Text Classification in Python
argilla
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Open-Source Data Collection Platform for LLM Fine-Tuning and RLHF
I'm Dani, CEO and co-founder of Argilla.
Happy to answer any questions you might have and excited to hear your thoughts!
More about Argilla
GitHub: https://github.com/argilla-io/argilla
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Meet Argilla: An Open-Source Data Curation Platform for Large Language Models (LLMs) and MLOps for Natural Language Processing
Github link: https://github.com/argilla-io/argilla
- Show HN: Argilla and AutoTrain – Train custom NLP models without code
- Rubrix release 0.17.0 with support for the spaCy training format
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No training data, no problem! Few-shot NER with a practical example
Rubrix, the open-source tool for data-centric NLP: https://github.com/recognai/rubrix
- [D] Expert Advice is needed on designing a feedback Loop for a (Textual Classification + NER) task in Production.
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[D] How should a former Web Developer, pursue career in Machine Learning?
E.g. https://github.com/recognai/rubrix
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[P] Small-Text: Active Learning for Text Classification in Python
I have already thought about providing an example of how to integrate small-text with one of the existing labeling tools, such as rubrix rubrix, but that hasn't been started yet.
- Finding and correcting text classification label errors with cleanlab and Rubrix | https://rubrix.readthedocs.io/en/master/tutorials/find_label_errors.html
- Rubrix: Open-source tool for building NLP training sets (now with weak supervision)
What are some alternatives?
transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
snorkel - A system for quickly generating training data with weak supervision
happy-transformer - Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
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.
doccano - Open source annotation tool for machine learning practitioners.
automl-docker - CLI-based tool to automatically build ML models from training data into a servable Docker container
cleanlab - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
DECIMER-Image_Transformer - DECIMER: Deep Learning for Chemical Image Recognition using Efficient-Net V2 + Transformer
data-centric-ai - Resources for Data Centric AI
MONAILabel - MONAI Label is an intelligent open source image labeling and learning tool.
trankit - Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing