Instructions to use lukaskim/SmileyLlama-1B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lukaskim/SmileyLlama-1B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="lukaskim/SmileyLlama-1B-GGUF",
	filename="SmileyLlama-1B-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 lukaskim/SmileyLlama-1B-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 lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf lukaskim/SmileyLlama-1B-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 lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf lukaskim/SmileyLlama-1B-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 lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf lukaskim/SmileyLlama-1B-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 lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf lukaskim/SmileyLlama-1B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/lukaskim/SmileyLlama-1B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use lukaskim/SmileyLlama-1B-GGUF with Ollama:
```
ollama run hf.co/lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
```

Unsloth Studio

How to use lukaskim/SmileyLlama-1B-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 lukaskim/SmileyLlama-1B-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 lukaskim/SmileyLlama-1B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for lukaskim/SmileyLlama-1B-GGUF to start chatting

How to use lukaskim/SmileyLlama-1B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf lukaskim/SmileyLlama-1B-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "lukaskim/SmileyLlama-1B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use lukaskim/SmileyLlama-1B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf lukaskim/SmileyLlama-1B-GGUF:Q4_K_M

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 lukaskim/SmileyLlama-1B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use lukaskim/SmileyLlama-1B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf lukaskim/SmileyLlama-1B-GGUF:Q4_K_M

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 "lukaskim/SmileyLlama-1B-GGUF:Q4_K_M" \
  --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"

Docker Model Runner
How to use lukaskim/SmileyLlama-1B-GGUF with Docker Model Runner:
```
docker model run hf.co/lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
```

Lemonade

How to use lukaskim/SmileyLlama-1B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull lukaskim/SmileyLlama-1B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.SmileyLlama-1B-GGUF-Q4_K_M

List all available models

lemonade list

SmileyLlama-1B-GGUF

GGUF quantizations of kysun63/smileyllama-1b-reproduced, a finetune of Llama-3.2-1B-Instruct.

Available quants

Quant	File
Q2_K	SmileyLlama-1B-Q2_K.gguf
Q4_K_M	SmileyLlama-1B-Q4_K_M.gguf
Q6_K	SmileyLlama-1B-Q6_K.gguf
Q8_0	SmileyLlama-1B-Q8_0.gguf
f16	SmileyLlama-1B-f16.gguf

SmileyLlama Prompt Template

Without properties,

### Instruction:
You love and excel at generating SMILES strings of drug-like molecules

### Input:
Output a SMILES string for a drug like molecule:

### Response:

With properties, where PROPERTY_LIST is a comma-space (", ".join()) separated list of the following options:

( <= 3, <= 4, <= 5, <= 7, > 7) H-bond donors
( <= 3, <= 4, <= 5, <= 10, <= 15) H-bond acceptors
( <= 300, <= 400, <= 500, <= 600, > 600) Molecular weight
( <= 3, <= 4, <= 5, <= 10, <= 15, > 15) logP
( <= 7, <= 10, > 10) Rotatable bonds
( < 0.4, > 0.4, > 0.5, > 0.6) Fraction sp3
( <= 90, <= 140, <= 200, > 200) TPSA
(a macrocycle, no macrocycles)
(has, lacks) bad SMARTS
lacks covalent warheads
has covalent warheads: (sulfonyl fluorides, acrylamides, ...)
A substructure of {SMILES_STRING}
A chemical of {CHEMICAL_FORMULA}

List of possible warheads:

sulfonyl fluorides: [#16](=[#8])(=[#8])-[#9]
chloroacetamides: [#8]=[#6](-[#6]-[#17])-[#7]
cyanoacrylamides: [#7]-[#6](=[#8])-[#6](-[#6]#[#7])=[#6]
epoxides: [#6]1-[#6]-[#8]-1
aziridines: [#6]1-[#6]-[#7]-1
disulfides: [#16]-[#16]
aldehydes: [#6](=[#8])-[#1]
vinyl sulfones: [#6]=[#6]-[#16](=[#8])(=[#8])-[#7]
boronic acids/esters: [#6]-[#5](-[#8])-[#8]
acrylamides: [#6]=[#6]-[#6](=[#8])-[#7]
cyanamides: [#6]-[#7](-[#6]#[#7])-[#6]
chloroFluoroAcetamides: [#7]-[#6](=[#8])-[#6](-[#9])-[#17]
butynamides: [#6]#[#6]-[#6](=[#8])-[#7]-[#6]
chloropropionamides: [#7]-[#6](=[#8])-[#6](-[#6])-[#17]
fluorosulfates: [#8]=[#16](=[#8])(-[#9])-[#8]
beta lactams: [#7]1-[#6]-[#6]-[#6]-1=[#8]

### Instruction:
You love and excel at generating SMILES strings of drug-like molecules

### Input:
Output a SMILES string for a drug like molecule with the following properties: {PROPERTY_LIST}:

### Response:

Downloads last month: 248

GGUF

Model size

1B params

Architecture

llama

Hardware compatibility

2-bit

4-bit

6-bit

8-bit

16-bit

Inference Providers NEW

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Model tree for lukaskim/SmileyLlama-1B-GGUF

Base model

meta-llama/Llama-3.2-1B-Instruct

Finetuned

kysun63/smileyllama-1b-reproduced

Quantized

(1)

this model

Collection including lukaskim/SmileyLlama-1B-GGUF

THG Llama Quants

Collection

3 items • Updated 8 days ago