Instructions to use Siddh07ETH/Pluto-Genesis-0.6B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Siddh07ETH/Pluto-Genesis-0.6B-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Siddh07ETH/Pluto-Genesis-0.6B-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Siddh07ETH/Pluto-Genesis-0.6B-GGUF", dtype="auto")

llama-cpp-python

How to use Siddh07ETH/Pluto-Genesis-0.6B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Siddh07ETH/Pluto-Genesis-0.6B-GGUF",
	filename="Pluto-Genesis-0.6B-F16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Siddh07ETH/Pluto-Genesis-0.6B-GGUF 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 Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Siddh07ETH/Pluto-Genesis-0.6B-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 Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Siddh07ETH/Pluto-Genesis-0.6B-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 Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use Siddh07ETH/Pluto-Genesis-0.6B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Siddh07ETH/Pluto-Genesis-0.6B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Siddh07ETH/Pluto-Genesis-0.6B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M

SGLang

How to use Siddh07ETH/Pluto-Genesis-0.6B-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Siddh07ETH/Pluto-Genesis-0.6B-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Siddh07ETH/Pluto-Genesis-0.6B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Siddh07ETH/Pluto-Genesis-0.6B-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Siddh07ETH/Pluto-Genesis-0.6B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use Siddh07ETH/Pluto-Genesis-0.6B-GGUF with Ollama:
```
ollama run hf.co/Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M
```

Unsloth Studio

How to use Siddh07ETH/Pluto-Genesis-0.6B-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 Siddh07ETH/Pluto-Genesis-0.6B-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 Siddh07ETH/Pluto-Genesis-0.6B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Siddh07ETH/Pluto-Genesis-0.6B-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use Siddh07ETH/Pluto-Genesis-0.6B-GGUF with Docker Model Runner:
```
docker model run hf.co/Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M
```

Lemonade

How to use Siddh07ETH/Pluto-Genesis-0.6B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Siddh07ETH/Pluto-Genesis-0.6B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Pluto-Genesis-0.6B-GGUF-Q4_K_M

List all available models

lemonade list

Pluto-Genesis-0.6B-GGUF

GGUF quantizations of Pluto-Genesis-0.6B, an instruction-tuned language model built on Qwen3-0.6B.

🤗 Original Transformers Model
https://huggingface.co/Siddh07ETH/Pluto-Genesis-0.6B

The original repository contains the FP16 model, training details, benchmarks, tokenizer, and Transformers checkpoints.

Model Links

Repository	Description
Original Model	https://huggingface.co/Siddh07ETH/Pluto-Genesis-0.6B
GGUF Repository	https://huggingface.co/Siddh07ETH/Pluto-Genesis-0.6B-GGUF

Overview

Pluto-Genesis-0.6B-GGUF provides optimized GGUF quantizations of the Pluto-Genesis-0.6B language model for efficient local inference.

These models are fully compatible with modern GGUF runtimes including:

llama.cpp
Ollama
LM Studio
Jan
KoboldCpp
text-generation-webui
GPT4All
Any GGUF-compatible inference engine

Available Quantizations

File	Quantization	Size	Recommended Use
`Pluto-Genesis-0.6B-F16.gguf`	F16	1.20 GB	Maximum quality, research and archival
`Pluto-Genesis-0.6B-Q8_0.gguf`	Q8_0	0.64 GB	Highest quality local inference
`Pluto-Genesis-0.6B-Q6_K.gguf`	Q6_K	0.50 GB	Excellent balance of quality and speed
`Pluto-Genesis-0.6B-Q5_K_M.gguf`	Q5_K_M	0.44 GB	Recommended for most users ⭐
`Pluto-Genesis-0.6B-Q4_K_M.gguf`	Q4_K_M	0.40 GB	Lowest memory usage and fastest inference

Quantization Guide

Quantization	Quality	Speed	Memory
F16	⭐⭐⭐⭐⭐	⭐⭐	Highest
Q8_0	⭐⭐⭐⭐☆	⭐⭐⭐	High
Q6_K	⭐⭐⭐⭐☆	⭐⭐⭐⭐	Medium
Q5_K_M	⭐⭐⭐⭐	⭐⭐⭐⭐⭐	Low
Q4_K_M	⭐⭐⭐	⭐⭐⭐⭐⭐	Lowest

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

Quick Start

llama.cpp

Download the recommended Q5_K_M model:

huggingface-cli download Siddh07ETH/Pluto-Genesis-0.6B-GGUF \
Pluto-Genesis-0.6B-Q5_K_M.gguf \
--local-dir ./models

Run inference:

llama-cli \
-m ./models/Pluto-Genesis-0.6B-Q5_K_M.gguf \
-p "<|im_start|>user
Explain quantum computing in simple terms.
<|im_end|>
<|im_start|>assistant" \
-n 256

Ollama

Create the model:

ollama create pluto-genesis-0.6b -f Modelfile

Run:

ollama run pluto-genesis-0.6b

Compatibility

These GGUF files have been generated for use with:

llama.cpp
Ollama
LM Studio
Jan
KoboldCpp
GPT4All
text-generation-webui

Conversion Details

Property	Value
Original Model	https://huggingface.co/Siddh07ETH/Pluto-Genesis-0.6B
GGUF Repository	https://huggingface.co/Siddh07ETH/Pluto-Genesis-0.6B-GGUF
Base Model	Qwen/Qwen3-0.6B
Format	GGUF
Conversion Tool	llama.cpp (`convert_hf_to_gguf.py`)
llama.cpp Version	`b5604`
Converted	2026-07-12T12:15:48Z

File Integrity

SHA-256 hashes for every GGUF file are available in:

CHECKSUMS.txt

Verify downloaded files before deployment for maximum integrity.

License

This project is distributed under the Apache License 2.0.

Please also review the license of the original base model:

Qwen/Qwen3-0.6B

Citation

If you use Pluto-Genesis in your research or applications, please cite:

@misc{pluto-genesis,
  title={Pluto-Genesis-0.6B},
  author={Siddh07ETH},
  year={2026},
  publisher={Hugging Face},
  howpublished={https://huggingface.co/Siddh07ETH/Pluto-Genesis-0.6B}
}

Author

Siddh07ETH

🤗 Original Model: https://huggingface.co/Siddh07ETH/Pluto-Genesis-0.6B
🤗 GGUF Repository: https://huggingface.co/Siddh07ETH/Pluto-Genesis-0.6B-GGUF

Built with Qwen3-0.6B, llama.cpp, and the open-source AI ecosystem.

Downloads last month: 174

GGUF

Model size

0.6B params

Architecture

qwen3

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

16-bit

Model tree for Siddh07ETH/Pluto-Genesis-0.6B-GGUF

Base model

Qwen/Qwen3-0.6B-Base

Finetuned

Qwen/Qwen3-0.6B

Quantized

(358)

this model