Update README: correct Modelfile template and add ollama example
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README.md
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@@ -21,46 +21,45 @@ This is a specialized **Text-to-SQL** model fine-tuned from the **Microsoft Phi-
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- **Training Technique:** Fine-tuned using Lora with [Unsloth](https://github.com/unslothai/unsloth).
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- **Format:** GGUF (Ready for Ollama, LM Studio, and llama.cpp)
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- **phi-3-mini-4k-instruct.Q4_K_M.gguf**
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- **phi-3-mini-4k-instruct.
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## Usage Instructions
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### Ollama (Recommended)
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To deploy locally:
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1. Download the `.gguf` file.
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2. Create the Modelfile with the following instructions
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```Dockerfile
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FROM ./phi-3-mini-4k-instruct.Q4_K_M.gguf
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{{ .System }}<|end|>
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<|user|>
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{{ .Prompt }}<|end|>
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<|assistant|>
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"""
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PARAMETER stop "<|end|>"
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PARAMETER
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PARAMETER
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PARAMETER
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```
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3. Run ```ollama create phi3-sql-expert -f Modelfile```
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5. Run ```ollama run phi3-sql-expert```
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## Evaluation Data
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The model was fine-tuned on the sql-create-context dataset, focusing on:
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- Mapping natural language to
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- Understanding table schemas provided in the prompt.
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- Maintaining strict SQL syntax.
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## Recommended Settings
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Temperature: 0.0 or 0.1 (SQL requires deterministic output).
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- **Training Technique:** Fine-tuned using Lora with [Unsloth](https://github.com/unslothai/unsloth).
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- **Format:** GGUF (Ready for Ollama, LM Studio, and llama.cpp)
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- **phi-3-mini-4k-instruct.Q4_K_M.gguf**
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- **phi-3-mini-4k-instruct.Q5_K.gguf**
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## Usage Instructions
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### Ollama (Recommended)
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To deploy locally:
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1. Download the `.gguf` file (Q4 or Q5).
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2. Create the Modelfile with the following instructions
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```Dockerfile
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FROM ./phi-3-mini-4k-instruct.Q4_K_M.gguf
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TEMPLATE """<s><|user|>
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Schema: {{ .System }}
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Question: {{ .Prompt }}<|end|>
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<|assistant|>
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"""
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# Parameters for SQL stability
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PARAMETER stop "<|end|>"
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PARAMETER stop "<s>"
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PARAMETER stop "</s>"
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PARAMETER temperature 0.0
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```
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3. Run ```ollama create phi3-sql-expert -f Modelfile```
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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?"```
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6. The answer should be ```SELECT nba_draft FROM table_name_7 WHERE school = "Northeast"```
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## Evaluation Data
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The model was fine-tuned on the [sql-create-context dataset](https://huggingface.co/datasets/b-mc2/sql-create-context), focusing on:
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- Mapping natural language to SQL queries with SELECT, WHERE, and JOIN statements.
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- Understanding table schemas provided in the prompt.
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- Maintaining strict SQL syntax in the response.
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## Recommended Settings
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Temperature: 0.0 or 0.1 (SQL requires deterministic output).
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