THG Llama Quants
Collection
3 items • Updated
How to use lukaskim/SmileyLlama-1B-GGUF with llama.cpp:
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
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
# 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
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
docker model run hf.co/lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
How to use lukaskim/SmileyLlama-1B-GGUF with Ollama:
ollama run hf.co/lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
How to use lukaskim/SmileyLlama-1B-GGUF with Pi:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
# Install Pi:
npm install -g @earendil-works/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"
}
]
}
}
}# Start Pi in your project directory: pi
How to use lukaskim/SmileyLlama-1B-GGUF with Docker Model Runner:
docker model run hf.co/lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
How to use lukaskim/SmileyLlama-1B-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
lemonade run user.SmileyLlama-1B-GGUF-Q4_K_M
lemonade list
How to use lukaskim/SmileyLlama-1B-GGUF with Hermes Agent:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
# 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
hermes
How to use lukaskim/SmileyLlama-1B-GGUF with OpenClaw:
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lukaskim/SmileyLlama-1B-GGUF:Q4_K_M
# 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
openclaw agent --local --agent main --message "Hello from Hugging Face"
GGUF quantizations of kysun63/smileyllama-1b-reproduced, a finetune of Llama-3.2-1B-Instruct.
| 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 |
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 SMARTSlacks covalent warheadshas covalent warheads: (sulfonyl fluorides, acrylamides, ...)A substructure of {SMILES_STRING}A chemical of {CHEMICAL_FORMULA}List of possible warheads:
[#16](=[#8])(=[#8])-[#9][#8]=[#6](-[#6]-[#17])-[#7][#7]-[#6](=[#8])-[#6](-[#6]#[#7])=[#6][#6]1-[#6]-[#8]-1[#6]1-[#6]-[#7]-1[#16]-[#16][#6](=[#8])-[#1][#6]=[#6]-[#16](=[#8])(=[#8])-[#7][#6]-[#5](-[#8])-[#8][#6]=[#6]-[#6](=[#8])-[#7][#6]-[#7](-[#6]#[#7])-[#6][#7]-[#6](=[#8])-[#6](-[#9])-[#17][#6]#[#6]-[#6](=[#8])-[#7]-[#6][#7]-[#6](=[#8])-[#6](-[#6])-[#17][#8]=[#16](=[#8])(-[#9])-[#8][#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:
2-bit
4-bit
6-bit
8-bit
16-bit
Base model
meta-llama/Llama-3.2-1B-Instruct