Instructions to use QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF",
	filename="Biggie-SmoLlm-0.15B-Base.Q2_K.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use QuantFactory/Biggie-SmoLlm-0.15B-Base-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-0.15B-Base-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/Biggie-SmoLlm-0.15B-Base-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-0.15B-Base-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/Biggie-SmoLlm-0.15B-Base-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-0.15B-Base-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/Biggie-SmoLlm-0.15B-Base-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-0.15B-Base-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF:Q4_K_M

Ollama
How to use QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF:Q4_K_M
```

Unsloth Studio

How to use QuantFactory/Biggie-SmoLlm-0.15B-Base-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-0.15B-Base-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-0.15B-Base-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-0.15B-Base-GGUF to start chatting

Docker Model Runner
How to use QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Biggie-SmoLlm-0.15B-Base-GGUF-Q4_K_M

List all available models

lemonade list

QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF

This is quantized version of nisten/Biggie-SmoLlm-0.15B-Base created using llama.cpp

Original Model Card

###EVEN SMALLER Frankenstein of smolLm-0.13b upped to 0.15b Use this frankenbase for training.

Done via semi-automated continuous merging to figure out the recipe. Model is more coherent.

wget https://huggingface.co/nisten/Biggie-SmoLlm-0.15B-Base/resolve/main/Biggie_SmolLM_0.15B_Base_bf16.gguf

llama-cli -ngl 99 -co --temp 0 -p "How to build a city on Mars via calculating Aldrin-Cycler orbits?" -m Biggie_SmolLM_0.15B
_Base_bf16.gguf

The temperature settings and min p etc need to be adjusted but even at default temp0 it was coherent for first 100 tokens. Amazing option for further training. And this is a merge of the base, not the instruct!

I don't understand how the f a 150mb file can talk but it can

Downloads last month: 746

GGUF

Model size

0.2B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Model tree for QuantFactory/Biggie-SmoLlm-0.15B-Base-GGUF

Base model

HuggingFaceTB/SmolLM-135M

Quantized

(22)

this model