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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ base_model: onekq-ai/OneSQL-v0.2-Qwen-3B
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+ tags:
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+ - text-generation-inference
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+ - transformers
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+ - qwen2
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+ - gguf
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+ license: apache-2.0
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+ language:
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+ - en
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+ ---
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+
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+ # Disclaimer
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+ Your email will be used for anonymous survey. It will not be shared with anyone.
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+
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+ # Introduction
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+
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+ This model is the GGUF version of [OneSQL-v0.2-Qwen-3B](https://huggingface.co/onekq-ai/OneSQL-v0.2-Qwen-3B).
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+
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+ # Performances
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+
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+ Below is the self-evaluation results for each quantization and improvement to [OneSQL-v0.1-Qwen-3B-GGUF](https://huggingface.co/onekq-ai/OneSQL-v0.1-Qwen-3B-GGUF).
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+
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+ | Quantization |EX score|v0.1 EX score
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+ |------------|-------|-------|
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+ | Q4_0 | 29.59 | 16.83 |
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+ | Q4_1 | 32.35 | 21.85 |
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+ | Q4_K_S | 31.16 | 22.49 |
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+ | Q4_K_M | 31.03 | 21.85 |
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+ | Q5_0 | 31.24 | 23.40 |
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+ | Q5_1 | 33.27 | 23.53 |
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+ | Q5_K_S | | 22.77 |
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+ | Q5_K_M | | 23.73 |
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+ | Q6_K | | 24.51 |
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+ | **Q8_0** | | **24.90** |
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+
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+ # Quick start
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+
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+ To use this model, craft your prompt to start with your database schema in the form of **CREATE TABLE**, followed by your natural language query preceded by **--**.
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+ Make sure your prompt ends with **SELECT** in order for the model to finish the query for you. There is no need to set other parameters like temperature or max token limit.
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+
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+ ```sh
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+ PROMPT="CREATE TABLE students (
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+ id INTEGER PRIMARY KEY,
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+ name TEXT,
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+ age INTEGER,
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+ grade TEXT
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+ );
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+
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+ -- Find the three youngest students
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+ SELECT "
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+
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+ PROMPT=$(printf "<|im_start|>system\nYou are a SQL expert. Return code only.<|im_end|>\n<|im_start|>user\n%s<|im_end|>\n<|im_start|>assistant\n" "$PROMPT")
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+
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+ llama.cpp/build/bin/llama-run file://OneSQL-v0.2-Qwen-1.5B-Q4_K_M.gguf "$PROMPT"
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+ ```
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+
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+ The model response is the finished SQL query without **SELECT**
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+ ```sql
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+ * FROM students ORDER BY age ASC LIMIT 3
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+ ```
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+
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+ # Caveats
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+
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+ * The performance drop from the original model is due to quantization itself, and the lack of beam search support in llama.cpp framework. Use at your own discretion.
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+ * The 2-bit and 3-bit quantizations suffer from repetitive and unrelevant output token, hence are not recommended for usage.