Instructions to use QuantFactory/Biggie-SmoLlm-0.4B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/Biggie-SmoLlm-0.4B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/Biggie-SmoLlm-0.4B-GGUF",
	filename="Biggie-SmoLlm-0.4B.Q2_K.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 QuantFactory/Biggie-SmoLlm-0.4B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/Biggie-SmoLlm-0.4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/Biggie-SmoLlm-0.4B-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 QuantFactory/Biggie-SmoLlm-0.4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/Biggie-SmoLlm-0.4B-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 QuantFactory/Biggie-SmoLlm-0.4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/Biggie-SmoLlm-0.4B-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 QuantFactory/Biggie-SmoLlm-0.4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/Biggie-SmoLlm-0.4B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/Biggie-SmoLlm-0.4B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/Biggie-SmoLlm-0.4B-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/Biggie-SmoLlm-0.4B-GGUF:Q4_K_M
```

Unsloth Studio

How to use QuantFactory/Biggie-SmoLlm-0.4B-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 QuantFactory/Biggie-SmoLlm-0.4B-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 QuantFactory/Biggie-SmoLlm-0.4B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for QuantFactory/Biggie-SmoLlm-0.4B-GGUF to start chatting

Docker Model Runner
How to use QuantFactory/Biggie-SmoLlm-0.4B-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/Biggie-SmoLlm-0.4B-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/Biggie-SmoLlm-0.4B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/Biggie-SmoLlm-0.4B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Biggie-SmoLlm-0.4B-GGUF-Q4_K_M

List all available models

lemonade list

QuantFactory/Biggie-SmoLlm-0.4B-GGUF

This is quantized version of nisten/Biggie-SmoLlm-0.4B created using llama.cpp

Original Model Card

###Coherent Frankenstein of smolLm-0.36b upped to 0.4b

This took about 5 hours of semi-automated continuous merging to figure out the recipe. Model is smarter, and UNTRAINED. Uploaded it for training. Yet it performs well as is even quantized to 8bit. 8bit gguf included for testing.

wget https://huggingface.co/nisten/Biggie-SmoLlm-0.4B/resolve/main/Biggie_SmolLM_400M_q8_0.gguf

./llama-cli -ngl 99 -co --temp 0 -p "How to build a city on Mars via calculating Aldrin-Cycler orbits?" -m Biggie_SmolLM_400M_q8_0.gguf -cnv -fa --keep -1

Downloads last month: 112

GGUF

Model size

0.4B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference Providers NEW

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Model tree for QuantFactory/Biggie-SmoLlm-0.4B-GGUF

Base model

HuggingFaceTB/SmolLM-360M

Quantized

HuggingFaceTB/SmolLM-360M-Instruct

Quantized

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