Add README

README.md

@@ -1,75 +1,23 @@
 ---
-license: mit
-base_model: microsoft/Phi-3-mini-4k-instruct
 tags:
-- text-to-sql
-- natural-language-to-sql
-- phi-3
-- unsloth
 - gguf
-- ollama
-- logic
-datasets:
-- b-mc2/sql-create-context
-language:
-- en
-library_name: unsloth
-pipeline_tag: text-generation
----
-
-# Phi-3-SQL-Expert (GGUF)
-
-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 (Optimized balance of speed and logic)
-- **Training Technique:** Fine-tuned using Lora with [Unsloth](https://github.com/unslothai/unsloth).
-- **Format:** GGUF (Ready for Ollama, LM Studio, and llama.cpp)
-
-## Usage Instructions
-
-### Ollama (Recommended)
-To deploy locally:
-
-1. Download the `.gguf` file.
-2. Create a file named `Modelfile` and paste the following:
-```dockerfile
-FROM ./phi3-sql-expert.Q4_K_M.gguf
-
-TEMPLATE """<|system|>
-You are a helpful assistant that writes SQL queries. Given a user question and a table schema, output only the SQL code.<|end|>
-<|user|>
-{{ .Prompt }}<|end|>
-<|assistant|>
-"""
-
-PARAMETER stop "<|end|>"
-PARAMETER temperature 0.1
-PARAMETER num_ctx 2048
-```
-
-3. Run ollama create sql-expert -f Modelfile
-
-4. Run ollama run sql-expert
-
-
-## Evaluation Data
-The model was fine-tuned on the sql-create-context dataset, focusing on:
-
-Mapping natural language to complex SELECT, WHERE, and JOIN statements.
-
-Understanding table schemas provided in the prompt.
+- llama.cpp
+- unsloth
 
-Maintaining strict SQL syntax.
+---
 
-## Recommended Settings
-Temperature: 0.0 or 0.1 (SQL requires deterministic output).
+# phi3-text2sql-lora : GGUF
 
-Stop Tokens: Ensure <|end|> is set as a stop sequence to prevent "infinite looping" generation.
+This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
 
-Context Window: 2048 or 4096 tokens.
+**Example usage**:
+- For text only LLMs:    `./llama.cpp/llama-cli -hf mrcmilo/phi3-text2sql-lora --jinja`
+- For multimodal models: `./llama.cpp/llama-mtmd-cli -hf mrcmilo/phi3-text2sql-lora --jinja`
 
-Model Developer: mrcmilo
+## Available Model files:
+- `phi-3-mini-4k-instruct.Q5_K.gguf`
 
-Base Model: Phi-3-mini-4k-instruct
+## Ollama
+An Ollama Modelfile is included for easy deployment.
+This was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)