Search Results for "quick shell rice"
Sort By:
Showing 6 open source projects for "quick shell rice"
View related business solutions-
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
Cut Cloud Costs with Google Compute EngineSave on compute costs with Compute Engine. Reduce your batch jobs and workload bill 60-91% with Spot VMs. Compute Engine's committed use offers customers up to 70% savings through sustained use discounts. Plus, you get one free e2-micro VM monthly and $300 credit to start.
-
1
runprompt
Run LLM prompts from your shell
runprompt is an interactive command launcher and prompt utility that lets users bind shell commands, scripts, and workflows to quick keyboard shortcuts or natural-language queries, helping streamline repetitive terminal tasks and boost developer productivity. It functions as a lightweight, launcher-centric interface where you can type a phrase, partial command, or alias and have RunPrompt suggest or execute relevant actions instantly, reducing the need to memorize long commands or navigate complex directory structures. ... -
2
gTTS
Python library and CLI tool to interface with Google Translate
...It supports customizable text pre-processors, which can correct pronunciations, tweak formatting, or handle domain-specific vocabulary before sending it to the API. gTTS is primarily aimed at developers who want a quick way to add cloud-backed speech to scripts, apps, or pipelines without managing any model weights locally. A small CLI utility, gtts-cli, makes it easy to test or batch-generate MP3 files right from the shell. -
3
ImageReward
[NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences
ImageReward is the first general-purpose human preference reward model (RM) designed for evaluating text-to-image generation, introduced alongside the NeurIPS 2023 paper ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation. Trained on 137k expert-annotated image pairs, ImageReward significantly outperforms existing scoring methods like CLIP, Aesthetic, and BLIP in capturing human visual preferences. It is provided as a Python package (image-reward) that enables... -
4
Tracking Any Point (TAP)
DeepMind model for tracking arbitrary points across videos & robotics
TAPNet is the official Google DeepMind repository for Tracking Any Point (TAP), bundling datasets, models, benchmarks, and demos for precise point tracking in videos. The project includes the TAP-Vid and TAPVid-3D benchmarks, which evaluate long-range tracking of arbitrary points in 2D and 3D across diverse real and synthetic videos. Its flagship models—TAPIR, BootsTAPIR, and the latest TAPNext—use matching plus temporal refinement or next-token style propagation to achieve state-of-the-art... -
Catch Bugs Before Your Customers DoMove from alert to fix before users notice. AppSignal monitors errors, performance bottlenecks, host health, and uptime—all from one dashboard. Instant notifications on deployments, anomaly triggers for memory spikes or error surges, and seamless log management. Works out of the box with Rails, Django, Express, Phoenix, Next.js, and dozens more. Starts at $23/month with no hidden fees.
-
5
Mini Agent
A minimal yet professional single agent demo project
Mini-Agent is a minimal yet production-minded demo project that shows how to build a serious command-line AI agent around the MiniMax-M2 model. It is designed both as a reference implementation and as a usable agent, demonstrating a full execution loop that includes planning, tool calls, and iterative refinement. The project exposes an Anthropic-compatible API interface and fully supports interleaved thinking, letting the agent alternate between reasoning steps and tool invocations during... -
6
Claude-Flow
The leading agent orchestration platform for Claude
Claude-Flow v2 Alpha is an advanced AI orchestration and automation framework designed for enterprise-grade, large-scale AI-driven development. It enables developers to coordinate multiple specialized AI agents in real time through a hive-mind architecture, combining swarm intelligence, neural reasoning, and a powerful set of 87 Modular Control Protocol (MCP) tools. The platform supports both quick swarm tasks and persistent multi-agent sessions known as hives, facilitating distributed AI...
- Previous
- You're on page 1
- Next
