awesome-ai-safety
refact
awesome-ai-safety | refact | |
---|---|---|
5 | 34 | |
138 | 1,428 | |
8.0% | 3.7% | |
5.6 | 9.8 | |
7 months ago | 7 days ago | |
JavaScript | ||
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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.
awesome-ai-safety
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Ask HN: Who is hiring? (October 2023)
Giskard - Testing framework for ML models| Multiple roles | Full-time | France | https://giskard.ai/
We are building the first collaborative & open-source Quality Assurance platform for all ML models - including Large Language Models.
Founded in 2021 in Paris by ex-Dataiku engineers, we are an emerging player in the fast-growing market of AI Quality & Safety.
Giskard helps Data Scientists & ML Engineering teams collaborate to evaluate, test & monitor AI models. We help organizations increase the efficiency of their AI development workflow, eliminate risks of AI biases and ensure robust, reliable & ethical AI models. Our open-source platform is used by dozens of ML teams across industries, both at enterprise companies & startups.
In 2022, we raised our first round of 1.5 million euros, led by Elaia, with participation from Bessemer and notable angel investors including the CTO of Hugging Face. To read more about this fundraising and how it will accelerate our growth, you can read this announcement: https://www.giskard.ai/knowledge/news-fundraising-2022
In 2023, we received a strategic investment from the European Commission to build a SaaS platform to automate compliance with the upcoming EU AI regulation. You can read more here: https://www.giskard.ai/knowledge/1-000-github-stars-3meu-and...
We are assembling a team of champions: Software Engineers, Machine Learning researchers, and Data Scientists ; to build our AI Quality platform and expand it to new types of AI models and industries. We have a culture of continuous learning & quality, and we help each other achieve high standards & goals!
We aim to grow from 15 to 25 people in the next 12 months. We're hiring the following roles:
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Ask HN: Who is hiring? (August 2023)
Giskard - Testing framework for ML models| Multiple roles | Full-time | France | https://giskard.ai/
We are building the first collaborative & open-source Quality Assurance platform for all ML models - including Large Language Models.
Founded in 2021 in Paris by ex-Dataiku engineers, we are an emerging player in the fast-growing market of AI Safety & Security.
Giskard helps Data Scientists & ML Engineering teams collaborate to evaluate, test & monitor AI models. We help organizations increase the efficiency of their AI development workflow, eliminate risks of AI biases and ensure robust, reliable & ethical AI models. Our open-source platform is used by dozens of ML teams across industries, both at enterprise companies & startups.
In 2022, we raised our first round of 1.5 million euros, led by Elaia, with participation from Bessemer and notable angel investors including the CTO of Hugging Face. To read more about this fundraising and how it will accelerate our growth, you can read this announcement: https://www.giskard.ai/knowledge/news-fundraising-2022
In 2023, we received a strategic investment from the European Commission to build a SaaS platform to automate compliance with the upcoming EU AI regulation. You can read more here: https://www.giskard.ai/knowledge/1-000-github-stars-3meu-and...
We are assembling a team of champions: Software Engineers, Machine Learning researchers, and Data Scientists ; to build our AI Quality platform and expand it to new types of AI models and industries. We have a culture of continuous learning & quality, and we help each other achieve high standards & goals!
We aim to grow from 15 to 25 people in the next 12 months. We're hiring the following roles:
* Software Engineer - https://apply.workable.com/giskard/j/AD2C90B581/ (Python, Java, Typescript, Vue.js, Cloud skills)
* Machine Learning Researcher - https://apply.workable.com/giskard/j/E89FE8E310/ (post-PhD)
* Data Science lead - https://apply.workable.com/giskard/j/E89FE8E310/ (ML + consulting experience required)
* Growth marketing intern - https://apply.workable.com/giskard/j/C8635E9B0C/
* Data Science intern - https://apply.workable.com/giskard/j/7F0B341852/
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Show HN: Python library to scan ML models for vulnerabilities
Hi! I’ve been working on this automatic scanner for ML models to detect issues like underperforming data slices, overconfidence in predictions, robustness problems, and others. It supports all main Python ML frameworks (sklearn, torch, xgboost, …) and integrates with the quality assurance solution we are building at Giskard AI (https://giskard.ai) to systematically test models before putting them in production.
It is still a beta and I would love to hear your feedback if you have the time to try it out.
We have quite a few tutorials in the docs with ready-made colab notebooks to make it easy to get started.
If you are interested in the code:
https://github.com/Giskard-AI/giskard/tree/main/python-clien...
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[R] Awesome AI Safety – A curated list of papers & technical articles on AI Quality & Safety
Repository: https://github.com/Giskard-AI/awesome-ai-safety
- AI Safety – curated papers for safer, ethical, and reliable AI
refact
- RefactAI: Use best-in-class LLMs for coding in your IDE
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Supercharge Your Dev Workflow: How Refact's AI-powered Code Completion Boosts Developer Productivity
With over 1.3k stars on GitHub, more than 40k downloads and installs on both VS Code and JetBrains IDEs, and more than 50 positive reviews, it is worth saying that Refact is part of the best product in the AI coding assistant market.
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What do you use to run your models?
On vscode i sometimes use continue.dev and refact.ai just for fun and they are great!
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AI Code assistant for about 50-70 users
Refact was made for this: https://github.com/smallcloudai/refact
- Free WebUI for Fine-Tuning and Self-Hosting Open-Source LLMs for Coding
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LocalPilot: Open-source GitHub Copilot on your MacBook
You should check-out [refact.ai](https://github.com/smallcloudai/refact). It has both autocomplete and chat. It's in active development, with lots of new features coming soon (context search, fine-tuning for larger models, etc)
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Replit's new AI Model now available on Hugging Face
I don’t recommend that, since that uses the cloud for the actual inference by default (and they provide no guidance for changing that).
I don’t consider cloud inference to count as getting it working “locally” as requested by the comment above yours.
Refact works nicely and works locally, but the challenge with any new model is making it be supported by the existing software: https://github.com/smallcloudai/refact/
- Refact.ai 1.0.0 Released
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📝 🚀 Creating our first documentation from scratch using Astro and Refact AI coding assistant
Previously, we used Astro for our refact.ai website and wanted to stay within the Astro ecosystem for the documentation.
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🤖We trained a small 1.6b code model and you can use it as a personal copilot in Refact for free🤖
Refact LLM can be easily integrated into existing developers workflows with an open-source docker container and VS Code and JetBrains plugins. With Refact's intuitive user interface, developers can utilize the model easily for a variety of coding tasks. Finetune is available in the self-hosting (docker) and Enterprise versions, making suggestions more relevant for your private codebase.
What are some alternatives?
opentofu - OpenTofu lets you declaratively manage your cloud infrastructure.
tabby - Self-hosted AI coding assistant
fauxpilot - FauxPilot - an open-source alternative to GitHub Copilot server
awesome-langchain - 😎 Awesome list of tools and projects with the awesome LangChain framework
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
giskard - 🐢 Open-Source Evaluation & Testing framework for LLMs and ML models
llama-cpp-python - Python bindings for llama.cpp
nl-wallet - NL Public Reference Wallet
developer - the first library to let you embed a developer agent in your own app!
mentat - Mentat - The AI Coding Assistant
supervision - We write your reusable computer vision tools. 💜