Instructions to use andhiyaulhaq/natural2sql 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 andhiyaulhaq/natural2sql 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 andhiyaulhaq/natural2sql:Q4_K_M # Run inference directly in the terminal: llama cli -hf andhiyaulhaq/natural2sql:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf andhiyaulhaq/natural2sql:Q4_K_M # Run inference directly in the terminal: llama cli -hf andhiyaulhaq/natural2sql:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf andhiyaulhaq/natural2sql:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf andhiyaulhaq/natural2sql:Q4_K_M
Use Docker
docker model run hf.co/andhiyaulhaq/natural2sql:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use andhiyaulhaq/natural2sql with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "andhiyaulhaq/natural2sql" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "andhiyaulhaq/natural2sql", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/andhiyaulhaq/natural2sql:Q4_K_M
- Ollama
How to use andhiyaulhaq/natural2sql with Ollama:
ollama run hf.co/andhiyaulhaq/natural2sql:Q4_K_M
- Unsloth Desktop
- Pi
How to use andhiyaulhaq/natural2sql with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf andhiyaulhaq/natural2sql: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": "andhiyaulhaq/natural2sql:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use andhiyaulhaq/natural2sql with Docker Model Runner:
docker model run hf.co/andhiyaulhaq/natural2sql:Q4_K_M
- Lemonade
How to use andhiyaulhaq/natural2sql with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull andhiyaulhaq/natural2sql:Q4_K_M
Run and chat with the model
lemonade run user.natural2sql-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use andhiyaulhaq/natural2sql with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf andhiyaulhaq/natural2sql: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 andhiyaulhaq/natural2sql:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use andhiyaulhaq/natural2sql with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf andhiyaulhaq/natural2sql: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 "andhiyaulhaq/natural2sql: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: 1,313 Bytes
df60d72 | 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 26 27 28 29 30 31 | FROM ./saved_finetuned_q4_k_m.gguf
# Refined System Instructions to allow for help/identity queries
SYSTEM """You are SQL-Llama, a specialized Text-to-SQL assistant.
CORE RULES:
1. If the user asks about your identity, capabilities, or how to use you, respond in natural language explaining that you generate SQL from a given 'Context' and 'Question'.
2. For all other inputs, you MUST output ONLY valid SQL code. Do not include markdown blocks, explanations, or conversational filler.
3. Required format for SQL generation:
Context: <schema>
Question: <natural language query>
If the required format is missing, politely ask the user to provide the Context and Question."""
TEMPLATE """<|begin_of_text|><|start_header_id|>system<|end_header_id|>
{{ .System }}<|eot_id|><|start_header_id|>user<|end_header_id|>
{{ .Prompt }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
"""
# Startup example to set expectations
MESSAGE user "How do I use you?"
MESSAGE assistant "I am SQL-Llama. To generate a query, please provide the database schema as 'Context' and your request as 'Question'. For example:\n\nContext: CREATE TABLE users (id INT, name TEXT);\nQuestion: Show all users."
PARAMETER temperature 0.1
PARAMETER top_p 0.95
PARAMETER stop "<|eot_id|>"
PARAMETER stop "<|start_header_id|>"
|