Alternatives
Products that do what Keys and Caches does
Vibe profile your ML models to get max performance.
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2018 · github.com
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2016 · github.com
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I built SpecMind, an open source developer tool for spec driven vibe coding. It keeps architecture and implementation aligned from the first commit instead of letting them drift apart. With AI assistants writing more of our code, projects move faster but architectural consistency is often lost. Each developer or AI can introduce new patterns, and after a few sprints, the structure becomes fragmented. SpecMind helps prevent that by generating and maintaining living architecture specs directly from your code. It works in three steps: 1. analyze – scans your codebase and generates…
Nov 2025 · github.com
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2021 · tensorbase.io
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While building a chat application I couldn't find find a free and opensource tool to store user sessions. This led to redcache-ai. The tool helps with semantic search, Retrieval Augmented Generation(RAG) and storage. This is an early version undergoing rapid iteration. Happy to answer questions and hear feedback.
2024 · github.com
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Vibe coded app that enables developers to quickly create so called "rules for AI" used by tools such as GitHub Copilot, Cursor and Windsurf, through an interactive, visual interface.
2025 · ai-rules-builder.pages.dev
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Hello HN. I'm Maxime, founder at LimaCharlie (https://limacharlie.io), a Hyperscaler for SecOps (access building blocks you need to build security operations, like AWS does for IT). We’ve engineered a new product on our platform that solves a timely issue acting as a guardrail between your AI and the world: Viberails (https://www.viberails.io) This won't be new to folks here, but we identified 4 challenges teams face right now with AI tools: 1. Auditing what the tools are doing. 2. Controlling toolcalls (and their impact on the world). 3. Centralized management. 4. Easy…
Feb 2026 · viberails.io
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Hey HN, when building ML systems for industrial AI, we have learned that data inspection is critical during the ML development process. We are also big fans of the Hugging Face ecosystem. That is why we built an integration to our data exploration tool Spotlight that allows you to interactively explore Hugging Face datasets with one line of code. Spotlight lets you leverage model results such as predictions and embeddings to gain a deeper understanding in data segments and model failure modes. Currently, many many NLP, CV, Audio and multimodal datasets are supported both locally and on the…
2023 · huggingface.co
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We built RapidFire AI, an open-source Python tool to speed up LLM fine-tuning and post-training with a powerful level of control not found in most tools: Stop, resume, clone-modify and warm-start configs on the fly—so you can branch experiments while they’re running instead of starting from scratch or running one after another. - Works within your OSS stack: PyTorch, HuggingFace TRL/PEFT), MLflow. - Hyperparallel search: launch as many configs as you want together, even on a single GPU - Dynamic real-time control: stop laggards, resume them later to revisit, branch promising configs in…
Sep 2025 · github.com
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Hi everyone, I've been working on a CLI tool that can help to easily run any model in claude, Codex, Gemini, Pi, and OpenCode. It's also an API keys manager, supports multiple providers or OpenAI/Claude/Gemini accounts. You can add openrouter, poe, Vercel AI gateways etc. It has a built-in provider that is free to all, which is using Deepseek-V4, no login or API key required, add your own when you're ready. After installation you can try claude instantly (No config, no login): aivo claude Hope it's useful to someone.
Apr 2026 · getaivo.dev
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Hello HN, We are pleased to introduce you graphlearn-for-pytorch (https://github.com/alibaba/graphlearn-for-pytorch), an open-source distributed graph neural network library based on PyTorch and compatible with PyG. Our library is designed to make it easy for developers to build and train large-scale graph models in a distributed environment. With graphlearn-for-pytorch, you can leverage GPUs to accelerate graph sampling and utilize UVA to reduce the overheads of feature collection. Following a scalable design, graphlearn-for-pytorch supports training GNN models on…
2023 · github.com
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We’re excited to share ML-Dev-Bench, a new open-source benchmark that tests AI agents on real-world ML development tasks. Unlike typical coding challenges or Kaggle-style competitions, our benchmark simulates end-to-end ML workflows including: - Dataset handling and preprocessing - Debugging model and code failures - Implementing new model architectures - Fine-tuning and improving existing models With 30 diverse tasks, ML-Dev-Bench evaluates agents across critical stages of ML development. To complement this, we built Calipers, a framework that provides systematic performance evaluation and…
2025 · github.com
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Hi HN, We're excited to introduce Fixstars AIBooster, our new performance engineering tool designed to significantly accelerate AI model training while optimizing GPU utilization. AIBooster provides: Real-time monitoring of GPU, CPU, memory, and power consumption. Clear visibility into performance bottlenecks, helping developers optimize AI workloads. Proven acceleration of AI training processes—users commonly achieve up to 2-3x speed improvements. Significant cost savings by maximizing infrastructure efficiency. It's free to try, requires minimal setup, and integrates seamlessly into your…
2025 · fixstars.com
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