--- tags: - gguf - llama.cpp - unsloth license: mit datasets: - b-mc2/sql-create-context language: - en metrics: - accuracy base_model: - microsoft/Phi-3-mini-4k-instruct --- This is a specialized **Text-to-SQL** model fine-tuned from the **Microsoft Phi-3-mini-4k-instruct** architecture. It has been optimized using **Unsloth** to provide high-accuracy SQL generation while remaining lightweight enough to run on consumer hardware. ## Key Features - **Architecture:** Phi-3-mini (3.8B parameters) - **Quantization:** Q4_K_M GGUF & Q5_K_M - **Training Technique:** Fine-tuned using Lora with [Unsloth](https://github.com/unslothai/unsloth). - **Format:** GGUF (Ready for Ollama, LM Studio, and llama.cpp) - **phi-3-mini-4k-instruct.Q4_K_M.gguf** - **phi-3-mini-4k-instruct.Q5_K.gguf** ## Usage Instructions ### Ollama (Recommended) To deploy locally: 1. Download the `.gguf` file (Q4 or Q5). 2. Create the Modelfile with the following instructions ```Dockerfile FROM ./phi-3-mini-4k-instruct.Q4_K_M.gguf TEMPLATE """<|user|> Schema: {{ .System }} Question: {{ .Prompt }}<|end|> <|assistant|> """ # Parameters for SQL stability PARAMETER stop "<|end|>" PARAMETER stop "" PARAMETER stop "" PARAMETER temperature 0.0 ``` 3. Run ```ollama create phi3-sql-expert -f Modelfile``` 5. Run ```ollama run phi3-sql-expert "schema: CREATE TABLE table_name_7 (nba_draft VARCHAR, school VARCHAR) question: What was the NBA draft status for Northeast High School?"``` 6. The answer should be ```SELECT nba_draft FROM table_name_7 WHERE school = "Northeast"``` ## Evaluation Data The model was fine-tuned on the [sql-create-context dataset](https://huggingface.co/datasets/b-mc2/sql-create-context), focusing on: - Mapping natural language to SQL queries with SELECT, WHERE, and JOIN statements. - Understanding table schemas provided in the prompt. - Maintaining strict SQL syntax in the response. ## Recommended Settings Temperature: 0.0 or 0.1 (SQL requires deterministic output). Stop Tokens: Ensure <|end|> is set as a stop sequence to prevent "infinite looping" generation. Context Window: 2048 tokens. **Model Developer**: [msquared](https://github.com/mrcmilano) Base Model: [Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)