argilla
skweak
| argilla | skweak | |
|---|---|---|
| 15 | 8 | |
| 3,122 | 910 | |
| 2.3% | 0.2% | |
| 9.8 | 6.2 | |
| 5 days ago | 6 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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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)
skweak
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Entity Extraction with Predefined List
Thanks for pointing me in the right direction. Seems like there’s a few other approaches with weak supervision: https://github.com/NorskRegnesentral/skweak
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[P] Programmatic: Powerful Weak Labeling
Code for https://arxiv.org/abs/2104.09683 found: https://github.com/NorskRegnesentral/skweak
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Show HN: Programmatic – a REPL for creating labeled data
Hi Raza here, one of the other co-founders.
I know that HN likes to nerd out over technical details so thought I’d share a bit more on how we aggregate the noisy labels to clean them up.
At the moment we use the great Skweak [1] open source library to do this. Skweak uses an HMM to infer the most likely unobserved label given the evidence of the votes from each of the labelling functions.
This whole strategy of first training a label model and then training a neural net was pioneered by Snorkel. We’ve used this approach for now but we actually think there are big opportunities for improvement.
We’re working on an end-to-end approach that de-noises the labelling function and trains the model at the same time. So far we’ve seen improvements on the standard benchmarks [2] and are planning to submit to Neurips.
R
[1]: Skweak package: https://github.com/NorskRegnesentral/skweak
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The hand-picked selection of the best Python libraries released in 2021
skweak.
- Skweak: Weak Supervision for NLP
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Inevitable Manual Work involved in NLP
For more advanced unsupervised labeling, you should check skweak
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How to get Training data for NER?
I'm the main developer behind skweak by the way, happy to hear you're interested in our toolkit :-) We do already have a small list of products (see https://github.com/NorskRegnesentral/skweak/blob/main/data/products.json) extracted from DBPedia and Wikidata, but it may not be exactly the type of products you're looking for.
What are some alternatives?
snorkel - A system for quickly generating training data with weak supervision
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
DearPy3D - Dear PyGui 3D Engine (prototyping)
doccano - Open source annotation tool for machine learning practitioners.
snorkel - A system for quickly generating training data with weak supervision [Moved to: https://github.com/snorkel-team/snorkel]
cleanlab - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
AugLy - A data augmentations library for audio, image, text, and video.
data-centric-ai - Resources for Data Centric AI
Text-Summarization-using-NLP - Text Summarization using NLP to fetch BBC News Article and summarize its text and also it includes custom article Summarization
trankit - Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing
gradio - Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!