Search Results for "kernel-br"
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Showing 9 open source projects for "kernel-br"
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1
JupyterLab LSP
Coding assistance for JupyterLab (code navigation + hover suggestions
...Use the context menu entry, or Alt + 🖱️ to jump to definitions/references (you can change it to Ctrl/⌘ in settings); use Alt + o to jump back. Place your cursor on a variable, function, etc and all the usages will be highlighted. When a kernel is available the suggestions from the kernel (such as keys of a dict and columns of a DataFrame) are merged with the suggestions from the Language Server (in notebook). If the kernel is too slow to respond promptly only the Language Server suggestions will be shown (default threshold: 0.6s). You can configure the completer to not attempt to fetch the kernel completions if the kernel is busy. -
2
RWKV Runner
A RWKV management and startup tool, full automation, only 8MB
...So it's combining the best of RNN and transformer - great performance, fast inference, fast training, saves VRAM, "infinite" ctxlen, and free text embedding. Moreover it's 100% attention-free. Default configs has enabled custom CUDA kernel acceleration, which is much faster and consumes much less VRAM. If you encounter possible compatibility issues, go to the Configs page and turn off Use Custom CUDA kernel to Accelerate. -
3
Embedding Atlas
Tool that provides interactive visualizations for large embeddings
Embedding Atlas is an open-source tool by Apple that provides scalable, interactive visualizations for large embedding datasets. It enables users to visualize, cross-filter, and search through embeddings alongside rich metadata, all in real time using modern web-based technologies. In addition to the command line tool, Embedding Atlas is also available as a Jupyter widget. Finally, components from Embedding Atlas are also available in an npm package. Order-independent transparency ensuring... -
4
sealos
Sealos is a production-ready Kubernetes distribution
A Cloud Operating System designed for managing cloud-native applications. Sealos['siːləs] is a cloud operating system distribution based on the Kubernetes kernel. Using the cloud like using a personal computer, reducing the cost of the cloud to 1/10 of the original. -
Run Any Workload on Compute Engine VMsCompute Engine delivers high-performance virtual machines for web apps, databases, containers, and AI workloads. Choose from general-purpose, compute-optimized, or GPU/TPU-accelerated machine types—or build custom VMs to match your exact specs. With live migration and automatic failover, your workloads stay online. New customers get $300 in free credits.
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5
polynote
A better notebook for Scala (and more)
...Designed to address shortcomings in classic notebook solutions, it blends features familiar from IDEs — such as smart autocomplete, parameter hints, and better runtime insights — with the flexibility of notebook workflows, enhancing both developer productivity and data exploration. Unlike many notebook environments that are tied to a single language kernel, Polynote tracks and manages state consistently across cells based on execution order and cell dependencies, which reduces hidden state and makes notebooks more reproducible and understandable. -
6
Yank Note
A Hackable Markdown Note Application for Programmers
...Version control, AI completion, mind map, documents encryption, code snippet running, integrated terminal, chart embedding, HTML applets, Reveal.js, plug-in, and macro replacement. Use Monaco kernel, optimize for Markdown editing, and have the same editing experience as VSCode. Support version control; Applets, runnable code blocks, tables, PlantUML, Drawio, macro replacements, etc., can be embedded in the document; support for OpenAI auto-completion. Data is saved as local Markdown files, and the extension functions are implemented in the original syntax of Markdown as far as possible. ... -
7
GPT-Code UI
An open source implementation of OpenAI's ChatGPT Code interpreter
An open source implementation of OpenAI's ChatGPT Code interpreter. Simply ask the OpenAI model to do something and it will generate & execute the code for you. You can put a .env in the working directory to load the OPENAI_API_KEY environment variable. For Azure OpenAI Services, there are also other configurable variables like deployment name. See .env.azure-example for more information. Note that model selection on the UI is currently not supported for Azure OpenAI Services. -
8
Cross Platform Node Guide
Improve front-end engineer workflow & standard, powered by TypeScript
...In addition to serving basic development workflows and specifications, Feflow provides an easy-to-expand plug-in mechanism for creating a team-wide toolchain ecosystem. Feflow only provides a CLI and kernel. The CLI is responsible for interacting with the command line terminal. -
9
Hydrogen
Run code interactively, inspect data, and plot
...You also may be interested in our latest project – interact – a desktop application that wraps up the best of the web-based Jupyter notebook. Watch expressions let you keep track of variables and re-run snippets after every change. Completions from the running kernel, just like autocomplete in the Chrome dev tools. Code can be inspected to show useful information provided by the running kernel. One kernel per language (so you can run snippets from several files, all in the same namespace). -
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