Instructions to use CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF", dtype="auto")

llama-cpp-python

How to use CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF",
	filename="qwen-3-4b-polyglot-r2-q4_k_m.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M

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 CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M

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 CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF with Ollama:
```
ollama run hf.co/CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M
```

Unsloth Studio

How to use CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF to start chatting

Docker Model Runner
How to use CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M
```

Lemonade

How to use CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF-Q4_K_M

List all available models

lemonade list

Polyglot r2

This model is a specialized fine-tune of Qwen-3 4b, optimized specifically for the Polyglot Air desktop application workflow. This version was trained on a dataset approximately 4 times larger than its predecessor, significantly expanding its range of commands and improving the accuracy of its responses.

It has been trained to strictly adhere to suffix-based commands, ensuring instant, clean, and direct responses without conversational filler, hallucinations, or "Here is the translation" preambles.

🎯 Purpose

The default chat models often struggle with context switching when presented with short strings followed by a command (e.g., text::en). They might explain the translation or chat with the user.

This model is fine-tuned to treat the ::suffix as a strict instruction code.

Input: O arquivo não pode ser salvo porque o disco está cheio::en
Output: The file cannot be saved because the disk is full

⚡ Suffix Command Table

Use these suffixes at the end of your selected text to trigger specific transformations.

Translation

Suffix	Action	Example Input	Model Output
`::en`	Translate to English	`Bom dia::en`	`Good morning`
`::pt`	Translate to Portuguese (Portugal)	`Good morning::pt`	`Bom dia`
`::ptbr`	Translate to Portuguese (Brazil)	`The bus is coming::ptbr`	`O ônibus está vindo`
`::es`	Translate to Spanish	`Hello friend::es`	`Hola amigo`
`::zh`	Translate to Chinese (Simplified)	`Hello::zh`	`你好`

Tone & Style Adjustment

Suffix	Action	Example Input	Model Output
`::fix`	Fix spelling and grammar	`i goes to skool yesterday::fix`	`I went to school yesterday`
`::formal`	Rewrite in a professional/formal tone	`Hey, send me that file asap::formal`	`Could you please send me that file as soon as possible?`
`::casual`	Rewrite in a casual tone	`I acknowledge receipt of your message::casual`	`Got your message, thanks!`
`::informal`	Rewrite in a slang/informal tone	`That is very interesting::informal`	`That's pretty cool`
`::polite`	Make polite	`I need the report now.::polite`	`Could you please provide the report when you have a moment?`
`::technical`	Make technical	`The computer is broken.::technical`	`The CPU is experiencing a critical hardware failure.`
`::creative`	Make creative	`The sun set.::creative`	`The sun painted the sky in hues of fire and gold.`
`::business`	Make business-oriented	`We should sell more.::business`	`We must optimize our sales funnel to increase revenue.`
`::news`	Rewrite in a news style	`A car crashed on the main street.::news`	`A vehicular collision occurred on Main Street earlier today.`
`::social`	Rewrite in a social media style	`I'm launching a new product.::social`	`🔥 BIG NEWS! So excited to launch our new product! #launch #new`

Content & Structure Manipulation

Suffix	Action	Example Input	Model Output
`::summarize`	Summarize the text	`[Long Text]::summarize`	`[Concise Summary]`
`::expand`	Expand / add details	`The project was a success.::expand`	`The project was a resounding success, exceeding all initial expectations.`
`::elaborate`	Elaborate / add details	`She was happy.::elaborate`	`A wide smile spread across her face, and her eyes sparkled with joy.`
`::simplify`	Simplify the text	`The confluence of factors precipitated this.::simplify`	`Many things caused this to happen.`
`::concise`	Make concise	`Due to the fact that it was raining, we left.::concise`	`We left because it was raining.`
`::toQuestion`	Transform into a question	`The report is due tomorrow.::toQuestion`	`Is the report due tomorrow?`
`::toStatement`	Transform into a statement	`Should we start the project?::toStatement`	`We should start the project.`

🚀 How to use with Polyglot Air

Download this model (or the GGUF version if available).
Add it to your Ollama library.
Open Polyglot Air.
Go to Settings > Model and select this model.
Enjoy seamless, instruction-following transformations.

Uploaded finetuned model

Developed by: CalmState
License: apache-2.0
Finetuned from model : unsloth/Qwen3-4B-Instruct-2507

This qwen3 model was trained 2x faster with Unsloth and Huggingface's TRL library.

Downloads last month: 18

GGUF

Model size

4B params

Architecture

qwen3

Hardware compatibility

4-bit

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Model tree for CalmState/Qwen-3-4b-Polyglot-r2-Q4_K_M-GGUF

Base model

Qwen/Qwen3-4B-Instruct-2507

Finetuned

unsloth/Qwen3-4B-Instruct-2507

Quantized

(32)

this model