open-source tool for data-centric NLP
Argilla is praised for its robust features, including native conversation handling, multimodal support, and seamless integration with the Hugging Face Hub, making it a powerful tool for managing AI datasets and enhancing model quality. Users appreciate its contributions to the open-source AI community, though details on its pricing were not mentioned, leaving its affordability unclear. The tool's updates, like progress tracking and improved import functionalities, are well-received, indicating a positive development pace. Overall, Argilla holds a strong reputation among users for its innovative capabilities in simplifying dataset creation and model fine-tuning processes.
Mentions (30d)
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GitHub Stars
4,911
478 forks
Argilla is praised for its robust features, including native conversation handling, multimodal support, and seamless integration with the Hugging Face Hub, making it a powerful tool for managing AI datasets and enhancing model quality. Users appreciate its contributions to the open-source AI community, though details on its pricing were not mentioned, leaving its affordability unclear. The tool's updates, like progress tracking and improved import functionalities, are well-received, indicating a positive development pace. Overall, Argilla holds a strong reputation among users for its innovative capabilities in simplifying dataset creation and model fine-tuning processes.
Features
Use Cases
Industry
information technology & services
Employees
4
Funding Stage
Merger / Acquisition
Total Funding
$16.9M
356
GitHub followers
86
GitHub repos
4,911
GitHub stars
20
npm packages
1
HuggingFace models
We're building FineWeb-Edu in many languages and need your help. This effort will help the Open-Source AI community close the language gap. Assamese is 99.4% done, French needs 64 more, Tamil: 216.
We're building FineWeb-Edu in many languages and need your help. This effort will help the Open-Source AI community close the language gap. Assamese is 99.4% done, French needs 64 more, Tamil: 216. Can you help us reach 1,000 annotations? https://t.co/fcnoQSKIuN
View originalExcited to introduce the new open-source tool from the @argilla_io team at @huggingface https://t.co/sBnfekGWpE https://t.co/PlBJvxAXJe
Excited to introduce the new open-source tool from the @argilla_io team at @huggingface https://t.co/sBnfekGWpE https://t.co/PlBJvxAXJe
View originalStart annotating: https://t.co/AGOeepDfHT
Start annotating: https://t.co/AGOeepDfHT
View originalWe're building FineWeb-Edu in many languages and need your help. This effort will help the Open-Source AI community close the language gap. Assamese is 99.4% done, French needs 64 more, Tamil: 216.
We're building FineWeb-Edu in many languages and need your help. This effort will help the Open-Source AI community close the language gap. Assamese is 99.4% done, French needs 64 more, Tamil: 216. Can you help us reach 1,000 annotations? https://t.co/fcnoQSKIuN
View originalGet started here: https://t.co/1zwkKZSeI6 Read the full blog post: https://t.co/lCY8uznkeA
Get started here: https://t.co/1zwkKZSeI6 Read the full blog post: https://t.co/lCY8uznkeA
View original🎯Synthetic Data Generator: A user-friendly app to build custom datasets with natural language! 👉 Ready to try it out? Links in comments https://t.co/Uh5NXKM8DN
🎯Synthetic Data Generator: A user-friendly app to build custom datasets with natural language! 👉 Ready to try it out? Links in comments https://t.co/Uh5NXKM8DN
View originalIf you're contributing to the @huggingface FineWeb 2 sprint, you can now share your progress with the world 👇 https://t.co/KchtKff8vE
If you're contributing to the @huggingface FineWeb 2 sprint, you can now share your progress with the world 👇 https://t.co/KchtKff8vE
View original@not_so_lain A worthy addition to a long list 🫶
@not_so_lain A worthy addition to a long list 🫶
View original@mervenoyann @huggingface Get involved https://t.co/gcl3TdiLRG
@mervenoyann @huggingface Get involved https://t.co/gcl3TdiLRG
View originalSupport the library to get more datasets like this: https://t.co/o8u9B2EYio
Support the library to get more datasets like this: https://t.co/o8u9B2EYio
View originalThe power of distilabel and well-curated datasets! Huge kudos to the SmolLM team, especially @gabrielmbmb, for crafting these beautiful synthetic datasets!
The power of distilabel and well-curated datasets! Huge kudos to the SmolLM team, especially @gabrielmbmb, for crafting these beautiful synthetic datasets!
View originalAre you using @argilla_io? If so, what are you missing? If not, what would make you start using it?
Are you using @argilla_io? If so, what are you missing? If not, what would make you start using it?
View original📢 Build datasets for AI on the @huggingface Hub—10x easier! How it works: 1. Pick a dataset—upload your own or choose from 240K open datasets 2. Paste the dataset ID and set up your labeling inter
📢 Build datasets for AI on the @huggingface Hub—10x easier! How it works: 1. Pick a dataset—upload your own or choose from 240K open datasets 2. Paste the dataset ID and set up your labeling interface 3. Share with your team or the whole community! https://t.co/ASw0vAV2PS
View originalThis is the 👆above synthetic dataset on @argilla_io for human review👇 https://t.co/HzsM2qDl2h
This is the 👆above synthetic dataset on @argilla_io for human review👇 https://t.co/HzsM2qDl2h
View originalShould we integrate synthetic data generation workflows into the @argilla_io UI? You describe the dataset in natural language, see some samples, tweak the data gen prompt, build the dataset, label a
Should we integrate synthetic data generation workflows into the @argilla_io UI? You describe the dataset in natural language, see some samples, tweak the data gen prompt, build the dataset, label a few samples, add those as few shots, add more human reviews from your team...
View originalRepository Audit Available
Deep analysis of argilla-io/argilla — architecture, costs, security, dependencies & more
Argilla uses a tiered pricing model. Visit their website for current pricing details.
Key features include: User-friendly interface for data annotation, Support for multiple data types including text, images, and audio, Integration with Hugging Face Hub for seamless model deployment, Collaborative annotation capabilities for teams, Version control for datasets, Customizable annotation templates, Real-time feedback and review system, API access for automated workflows.
Argilla is commonly used for: Training NLP models with labeled datasets, Creating high-quality training data for machine learning, Conducting sentiment analysis on social media data, Building chatbots with domain-specific knowledge, Developing named entity recognition systems, Enhancing data quality for research projects.
Argilla integrates with: Hugging Face Hub, TensorFlow, PyTorch, Jupyter Notebooks, Google Cloud Storage, AWS S3, Slack for team notifications, GitHub for version control, Zapier for workflow automation, Docker for containerization.
Argilla has a public GitHub repository with 4,911 stars.
Based on 57 social mentions analyzed, 4% of sentiment is positive, 96% neutral, and 0% negative.
