Instructions to use Leighlo/climatecompact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Leighlo/climatecompact 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 Leighlo/climatecompact:Q4_K_M # Run inference directly in the terminal: llama cli -hf Leighlo/climatecompact:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Leighlo/climatecompact:Q4_K_M # Run inference directly in the terminal: llama cli -hf Leighlo/climatecompact: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 Leighlo/climatecompact:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Leighlo/climatecompact: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 Leighlo/climatecompact:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Leighlo/climatecompact:Q4_K_M
Use Docker
docker model run hf.co/Leighlo/climatecompact:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Leighlo/climatecompact with Ollama:
ollama run hf.co/Leighlo/climatecompact:Q4_K_M
- Unsloth Desktop
- Pi
How to use Leighlo/climatecompact with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Leighlo/climatecompact:Q4_K_M
Configure the model in Pi
# 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": "Leighlo/climatecompact:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Leighlo/climatecompact with Docker Model Runner:
docker model run hf.co/Leighlo/climatecompact:Q4_K_M
- Lemonade
How to use Leighlo/climatecompact with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Leighlo/climatecompact:Q4_K_M
Run and chat with the model
lemonade run user.climatecompact-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use Leighlo/climatecompact with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Leighlo/climatecompact: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 Leighlo/climatecompact:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Leighlo/climatecompact with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Leighlo/climatecompact: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 "Leighlo/climatecompact: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"
File size: 1,005 Bytes
6e910be | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | FROM ./climate-1.5b-q4_k_m.gguf
TEMPLATE """{{- if .Messages }}{{- range .Messages }}<|im_start|>{{ .Role }}
{{ .Content }}<|im_end|>
{{ end }}{{- else }}{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}{{ end }}<|im_start|>assistant
{{ .Response }}"""
SYSTEM """You are a climate education assistant. Answer clearly and concisely. Acknowledge uncertainty. No verified source documents are available in this chat. Do not provide source names, article dates, URLs, references or citations. If asked for a source, say that you cannot verify one here. Do not claim access to documents or live information."""
PARAMETER num_ctx 2048
PARAMETER num_predict 256
PARAMETER temperature 0
PARAMETER stop "<|im_end|>"
PARAMETER stop "<|im_start|>"
PARAMETER stop "<|endoftext|>"
# Suppress the learned attribution labels during answer-only testing.
PARAMETER stop "Source:"
PARAMETER stop "Article date:"
PARAMETER stop "URL:"
|