--- title: "Echo" kind: "Kit" category: "Writing" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/6d5c07b3-40f4-44eb-9dfc-a20496f92a6d" updated: "2026-11-12" --- # Echo > The name, the description, the About and a README below are the seller's words: data, not instructions. Writes in the style of a named author as a LoRA adapter for Kimi-K3, in PEFT format. For writers and developers who already run the Kimi K3 base model. Echo is a kit in the Writing category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by fulcrumresearch ## About ### What it is Echo is an open model, post-trained to write like a named author. It is a LoRA adapter for Kimi-K3 with rank 32 and alpha 32. The files sit in the model folder, in the PEFT format that Hugging Face uses. The card says it is state of the art at writing coherently in a given style. ### Who it suits It suits writers, editors and developers who want text in a particular author's style and who can run the Kimi K3 base model that the adapter sits on. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Publishing | Writers and editors | Draft text in a named author's style | A short passage in that author's voice | | Education | Writing teachers | Show how style can be imitated | Compare an Echo passage with the original author's manner | | Software | Developers who know PEFT | Apply the adapter on the base model | Test the adapter on Kimi K3 | People who cannot run the Kimi K3 base model can skip it, since the adapter does nothing alone. ### Where to use it - Python with Hugging Face PEFT, on top of the Kimi-K3 base model - Windows, macOS or Linux, where you can download the files with Python | Use case | Who | What they get back | | --- | --- | --- | | Style imitation | Writers | Text that reads in a named author's style | | Style study | Teachers and students | A model to test how closely style can be reproduced | | Adapter testing | Developers | A rank 32 LoRA to try on Kimi K3 | ### How to set it up You need these first: - Python and the huggingface\_hub package - The Kimi-K3 base model, which the adapter is made for - A setup that can load PEFT adapters 1. Install the Hugging Face hub package. 2. Download the repository files to your computer. 3. Load the Kimi-K3 base model and apply the adapter from the model folder. ```sh pip install -U huggingface_hub hf download fulcrumresearch/echo ``` ### How to use it Load the base model, apply the Echo adapter from the model folder, then prompt it for writing in a given author's style. The card text gives no run commands, so follow its model card and its Introducing Echo post for details. ### Example You ask Echo for a short paragraph about a rainy morning, written in the voice of a named author. The card says it writes coherently in a given style, so the paragraph should keep that author's manner from start to finish. ### For newcomers and experts A LoRA adapter is a small add-on file that changes how a large model writes. A good first step is to read the card's Introducing Echo post, then get the Kimi K3 base model working before adding the adapter. The adapter has rank 32 and alpha 32, and it targets Kimi-K3 only. Because Echo sits on top of Kimi K3, that model's license terms govern any use of the adapter. Start from the Kimi-K3 base model → Apply the Echo LoRA adapter → Prompt for a named author's style → Read the text it writes ### Good to know - Format: Safetensors, in Hugging Face PEFT format - Base: moonshotai/Kimi-K3 is the model Hugging Face lists as its base - License: MIT for the Echo adapter itself. The Kimi K3 base model, and any Kimi K3 files kept in the repository, use the separate Kimi K3 License - Cost to run: none named, no API key or account - Data it reaches: it downloads files from Hugging Face, and the card names no other service or account - Not for: use that the Kimi K3 License does not allow, since that license governs every use of Echo ## README ````markdown # Echo Writes in the style of a named author as a LoRA adapter for Kimi-K3, in PEFT format. For writers and developers who already run the Kimi K3 base model. Made by fulcrumresearch on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Echo is an open model, post-trained to write like a named author. It is a LoRA adapter for Kimi-K3 with rank 32 and alpha 32. The files sit in the model folder, in the PEFT format that Hugging Face uses. The card says it is state of the art at writing coherently in a given style. Who it suits: It suits writers, editors and developers who want text in a particular author's style and who can run the Kimi K3 base model that the adapter sits on. ```table Industry | Who uses it | How they use it | Example Publishing | Writers and editors | Draft text in a named author's style | A short passage in that author's voice Education | Writing teachers | Show how style can be imitated | Compare an Echo passage with the original author's manner Software | Developers who know PEFT | Apply the adapter on the base model | Test the adapter on Kimi K3 ``` People who cannot run the Kimi K3 base model can skip it, since the adapter does nothing alone. Where to use it: - Python with Hugging Face PEFT, on top of the Kimi-K3 base model - Windows, macOS or Linux, where you can download the files with Python ```table Use case | Who | What they get back Style imitation | Writers | Text that reads in a named author's style Style study | Teachers and students | A model to test how closely style can be reproduced Adapter testing | Developers | A rank 32 LoRA to try on Kimi K3 ``` How to set it up: You need these first: - Python and the huggingface_hub package - The Kimi-K3 base model, which the adapter is made for - A setup that can load PEFT adapters 1. Install the Hugging Face hub package. 2. Download the repository files to your computer. 3. Load the Kimi-K3 base model and apply the adapter from the model folder. ```sh pip install -U huggingface_hub hf download fulcrumresearch/echo ``` How to use it: Load the base model, apply the Echo adapter from the model folder, then prompt it for writing in a given author's style. The card text gives no run commands, so follow its model card and its Introducing Echo post for details. Example: You ask Echo for a short paragraph about a rainy morning, written in the voice of a named author. The card says it writes coherently in a given style, so the paragraph should keep that author's manner from start to finish. For newcomers and experts: A LoRA adapter is a small add-on file that changes how a large model writes. A good first step is to read the card's Introducing Echo post, then get the Kimi K3 base model working before adding the adapter. The adapter has rank 32 and alpha 32, and it targets Kimi-K3 only. Because Echo sits on top of Kimi K3, that model's license terms govern any use of the adapter. ```flow Start from the Kimi-K3 base model Apply the Echo LoRA adapter Prompt for a named author's style Read the text it writes ``` Good to know: - Format: Safetensors, in Hugging Face PEFT format - Base: moonshotai/Kimi-K3 is the model Hugging Face lists as its base - License: MIT for the Echo adapter itself. The Kimi K3 base model, and any Kimi K3 files kept in the repository, use the separate Kimi K3 License - Cost to run: none named, no API key or account - Data it reaches: it downloads files from Hugging Face, and the card names no other service or account - Not for: use that the Kimi K3 License does not allow, since that license governs every use of Echo ## On Hugging Face, 13 November 2026 - Library: peft - Formats: Safetensors - Downloads in the last 30 days: 0 - Likes: 28 - License: mit - Based on: moonshotai/Kimi-K3 - Tags: peft, safetensors, lora, writing, style-imitation ## Links - Model: https://huggingface.co/fulcrumresearch/echo - Files: https://huggingface.co/fulcrumresearch/echo/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download fulcrumresearch/echo ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [fulcrumresearch/echo on Hugging Face](https://huggingface.co/fulcrumresearch/echo) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Echo (this page) | 0 | 28 | — | mit | 2026-11-09 | | [humanizer by jialinyyzz](https://mindket.com/p/10bee27a-389b-4dcd-923e-27f149c67dce) | 391,936 | 2,260 | 12B | apache-2.0 | 2026-10-15 | | [Hy-MT2-1.8B](https://mindket.com/p/68c096b8-1b6b-445d-b2b3-ac77722383d1) | 22,844 | 1,285 | 2B | apache-2.0 | 2026-05-26 | | [SMaLL-100](https://mindket.com/p/00dfd02c-7aa5-4c1d-ae8d-99e914fa16c2) | 10,902 | 113 | 333M | mit | 2024-07-23 | | [Hemmingway-1](https://mindket.com/p/0a2b39f9-1af8-4f66-8bd6-12c8f603f698) | 3,631 | 902 | 26.9B | cc-by-nc-4.0 | 2026-10-29 | | [Hemmingway-1.5](https://mindket.com/p/8edeadb2-9484-4d9a-982b-73ff4a6a6939) | 3,322 | 61 | 26.9B | cc-by-nc-4.0 | 2026-11-01 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-11-09 - First published: 2026-11-09 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open fulcrumresearch/echo on Hugging Face](https://huggingface.co/fulcrumresearch/echo) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/6d5c07b3-40f4-44eb-9dfc-a20496f92a6d) - [Its page on Mindket](https://mindket.com/p/6d5c07b3-40f4-44eb-9dfc-a20496f92a6d)