Text Generation
Safetensors
GGUF
English
qwen2
text-to-sql
sql-generation
natural-language-to-sql
deepseek
qwen
reasoning
database
conversational
Instructions to use DeepSQL/DeepSQL-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use DeepSQL/DeepSQL-1.0 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="DeepSQL/DeepSQL-1.0", filename="deepsql-1.0.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use DeepSQL/DeepSQL-1.0 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf DeepSQL/DeepSQL-1.0 # Run inference directly in the terminal: llama-cli -hf DeepSQL/DeepSQL-1.0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf DeepSQL/DeepSQL-1.0 # Run inference directly in the terminal: llama-cli -hf DeepSQL/DeepSQL-1.0
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 DeepSQL/DeepSQL-1.0 # Run inference directly in the terminal: ./llama-cli -hf DeepSQL/DeepSQL-1.0
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 DeepSQL/DeepSQL-1.0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf DeepSQL/DeepSQL-1.0
Use Docker
docker model run hf.co/DeepSQL/DeepSQL-1.0
- LM Studio
- Jan
- vLLM
How to use DeepSQL/DeepSQL-1.0 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DeepSQL/DeepSQL-1.0" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DeepSQL/DeepSQL-1.0", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/DeepSQL/DeepSQL-1.0
- Ollama
How to use DeepSQL/DeepSQL-1.0 with Ollama:
ollama run hf.co/DeepSQL/DeepSQL-1.0
- Unsloth Studio new
How to use DeepSQL/DeepSQL-1.0 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 DeepSQL/DeepSQL-1.0 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 DeepSQL/DeepSQL-1.0 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for DeepSQL/DeepSQL-1.0 to start chatting
- Docker Model Runner
How to use DeepSQL/DeepSQL-1.0 with Docker Model Runner:
docker model run hf.co/DeepSQL/DeepSQL-1.0
- Lemonade
How to use DeepSQL/DeepSQL-1.0 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull DeepSQL/DeepSQL-1.0
Run and chat with the model
lemonade run user.DeepSQL-1.0-{{QUANT_TAG}}List all available models
lemonade list
| { | |
| "_name_or_path": "./models/DeepSeek-R1-Distill-Qwen-1.5B", | |
| "architectures": [ | |
| "Qwen2ForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 151643, | |
| "eos_token_id": 151643, | |
| "hidden_act": "silu", | |
| "hidden_size": 1536, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 8960, | |
| "max_position_embeddings": 131072, | |
| "max_window_layers": 21, | |
| "model_type": "qwen2", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 28, | |
| "num_key_value_heads": 2, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 10000, | |
| "sliding_window": null, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.48.2", | |
| "use_cache": false, | |
| "use_mrope": false, | |
| "use_sliding_window": false, | |
| "vocab_size": 151936 | |
| } | |