Instructions to use kolada-app/Kolada-writer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use kolada-app/Kolada-writer with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf kolada-app/Kolada-writer # Run inference directly in the terminal: llama cli -hf kolada-app/Kolada-writer
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf kolada-app/Kolada-writer # Run inference directly in the terminal: llama cli -hf kolada-app/Kolada-writer
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf kolada-app/Kolada-writer # Run inference directly in the terminal: ./llama-cli -hf kolada-app/Kolada-writer
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf kolada-app/Kolada-writer # Run inference directly in the terminal: ./build/bin/llama-cli -hf kolada-app/Kolada-writer
Use Docker
docker model run hf.co/kolada-app/Kolada-writer
- Llama new
- LM Studio
- Jan
- vLLM
How to use kolada-app/Kolada-writer with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kolada-app/Kolada-writer" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kolada-app/Kolada-writer", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/kolada-app/Kolada-writer
- Ollama
How to use kolada-app/Kolada-writer with Ollama:
ollama run hf.co/kolada-app/Kolada-writer
- Unsloth Desktop
- Pi
How to use kolada-app/Kolada-writer with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kolada-app/Kolada-writer
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "kolada-app/Kolada-writer" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use kolada-app/Kolada-writer with Docker Model Runner:
docker model run hf.co/kolada-app/Kolada-writer
- Lemonade
How to use kolada-app/Kolada-writer with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kolada-app/Kolada-writer
Run and chat with the model
lemonade run user.Kolada-writer-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use kolada-app/Kolada-writer with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kolada-app/Kolada-writer
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default kolada-app/Kolada-writer
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use kolada-app/Kolada-writer with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kolada-app/Kolada-writer
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "kolada-app/Kolada-writer" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Kolada Writer
The AI writing assistant inside Kolada, a notes app. It fixes typos, spelling and grammar as you write, using what you wrote earlier in the note to get names and words right, and it writes a one-line summary of longer notes. It runs on your own computer, so your notes never leave it.
Two sizes, the same skills:
| File | Size | For | |
|---|---|---|---|
| Light | Kolada-writer-light-v1.gguf |
219 MB | Any computer; quickest |
| Full | Kolada-writer-full-v1.gguf |
697 MB | Sharper fixes and summaries |
Both write in English, Arabic, French, German, Spanish, Portuguese, Chinese, Japanese and Korean.
How to use it
It answers with the corrected text and nothing else. Ask in ChatML:
<|im_start|>system
Correct typos, spelling and grammar. Change nothing else.<|im_end|>
<|im_start|>user
{the paragraph before, as it is}<|im_end|>
<|im_start|>assistant
{the same paragraph, unchanged}<|im_end|>
<|im_start|>user
{the paragraph to correct}
(Not in the dictionary: {word} (maybe {guess} or {guess}), ...)<|im_end|>
<|im_start|>assistant
- The paragraph before (the user/assistant pair) is optional. Include it when there is one: it is how the model knows names and words used earlier in the note.
- The dictionary line is optional too. If a spell checker is at hand, list the words it does not know with its first guesses (at most six words, two guesses each). The model weighs them against the sentence; without them it fixes on its own.
- Greedy decoding (temperature 0). Stop at
<|im_end|>. - Pieces that must never change (links, code, tags) can be replaced by markers
โฆ1โง,โฆ2โงโฆ before asking, and put back after.
For a summary, ask with this system turn and the note as the user's message:
You write the gist of notes: one line of 5 to 12 words saying what the user's note is about, like a subtitle. The note is in English: write the line in English. Never just a title of a word or two, never a sentence about the note, no quotes, no full stop.
With llama.cpp:
llama-cli -m Kolada-writer-full-v1.gguf -no-cnv --temp 0 -f prompt.txt
In Kolada, every fix is also checked before it lands: the original wording is kept unless the model is sure of its change, and no link, number or name it was not asked about is touched. Used on its own, the model has none of those checks, so review what it changes.
Training
- Data: notes written for training in the nine languages by Qwen3-30B-A3B-Instruct-2507 (Apache 2.0), given the mistakes each language is really typed with, by rule (neighbouring keys on each keyboard layout, accents, hamza, spacing, input-method characters) and by the same model listing realistic slips; real typo fixes from the GitHub Typo Corpus; sentences from Tatoeba (CC BY 2.0 FR) and Wikipedia (CC BY-SA 4.0). Many examples are text already right that must come back unchanged. Summaries were written by the same Qwen model and kept only where Kolada would show them.
- Method: every weight fine-tuned (Full from LFM2.5-1.2B-Instruct, Light from LFM2.5-350M), then quantized to Q4_K_M with llama.cpp.
- No user data: no one's notes were used, at any stage.
Limits
- It misses some mistakes, more often in Chinese, Japanese and Korean than in the other languages.
- It can change a line that was already right. Kolada holds such changes back; used directly, review its changes.
- Arabic: written for Modern Standard Arabic; spoken dialects are not corrected reliably.
- Meant for short paragraphs, as in notes; send longer text a paragraph at a time.
- Not a rewriter: it does not restyle or rephrase.
License
- The models: CC BY-NC 4.0. Use, share and adapt them for non-commercial purposes, with attribution to Kolada. For commercial use, ask Kolada through kolada.app.
- The base models: derivatives of LFM2.5-350M and LFM2.5-1.2B-Instruct, so the LFM Open License v1.0 applies as well, including its notices and its revenue threshold.
- Endorsement: Liquid AI has not reviewed or endorsed these models. NOTICE lists the changes made.
Citation
@misc{kolada-writer-v1,
title = {Kolada Writer: on-device writing help for notes},
author = {Kolada},
year = {2026},
url = {https://huggingface.co/kolada-app/Kolada-writer}
}
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Model tree for kolada-app/Kolada-writer
Base model
LiquidAI/LFM2.5-1.2B-Base