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.ipynb_checkpoints/README-checkpoint.md

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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- Qwen/Qwen3-4B-Thinking-2507
+pipeline_tag: text-generation
+library_name: transformers
+---
+# Lightning-4b - Your Local data analysis agent
+
+[![GitHub](https://img.shields.io/badge/GitHub-Repository-blue?logo=github)](https://github.com/quelmap-inc/quelmap) 
+[![License](https://img.shields.io/badge/License-Apache%202.0-yellow)](https://opensource.org/licenses/Apache-2.0)
+
+![image/svg](assets/lightning-logo2.svg)
+
+## Overview
+Lightning-4b is a language model specifically designed and trained for data analysis tasks on local devices. With just a laptop (fully tested on an M4 MacBook Air with 16GB RAM), you can process data without ever sending it to major LLM provider.
+### What it can do
+- Data visualization    
+- Table joins
+- t-tests
+- Unlimited rows, 30+ tables analyzed simultaneously
+### What it cannot do
+- Business reasoning or management decision-making advice
+- Multi-turn analysis
+
+To use this model, install [quelmap](https://github.com/quelmap-inc/quelmap) on your device.  
+Quelmap is an open-source data analysis assistant with every essential features like data upload and an built-in python sandbox.  
+For installation instructions, see the [Quick Start](https://github.com/quelmap-inc/quelmap).
+![image/gif](.assets/preview.gif)
+### Performance
+This model was trained specifically for use with [quelmap](https://github.com/quelmap-inc/quelmap).  
+It was evaluated using a sample database and 122 analysis queries, and achieved performance surpassing models with **50x more parameters**.
+
+For details about the model and its training process, see the [Lightning-4b Details](https://quelmap.com/lightinig-4b) page.
+
+![image/svg](.assets/lightning.svg)
+
+### Running Model on your machine
+You can easily install Lightning-4b and quelmap by following the [Quick Start](https://github.com/quelmap-inc/quelmap).
+
+Lightning-4b has multiple quantization versions depending on your hardware.  
+It runs smoothly on laptops, and on higher-spec machines it can handle more tables (30+ tables) and longer chat histories.
+
+Example Specs and Model Versions
+- Laptop (e.g. mac book air 16GB) - 4bit Quantization + 10,240 Context Window
+```
+ollama pull hf.co/quelmap/Lightning-4b-GGUF-short-ctx:Q4_K_M
+```
+- Gaming Laptop - 4bit Quantization + 40,960 Context Window
+```
+ollama pull hf.co/quelmap/Lightning-4b-GGUF:Q4_K_M
+```
+- Powerful PC with GPU - No Quantization + 40,960 Context Window
+```
+ollama pull hf.co/quelmap/Lightning-4b-GGUF:F16
+```
+
+For more details, please refer to the  [Lightning-4b Details](https://quelmap.com/lightinig-4b) page.

.ipynb_checkpoints/params-checkpoint

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+{
+    "temperature": 0.2,
+    "min_p" : 0.00,
+    "top_k" : 20,
+    "top_p" : 0.95,
+    "num_ctx" : 40960
+}

README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- Qwen/Qwen3-4B-Thinking-2507
+pipeline_tag: text-generation
+library_name: transformers
+---
+# Lightning-4b - Your Local data analysis agent
+
+[![GitHub](https://img.shields.io/badge/GitHub-Repository-blue?logo=github)](https://github.com/quelmap-inc/quelmap) 
+[![License](https://img.shields.io/badge/License-Apache%202.0-yellow)](https://opensource.org/licenses/Apache-2.0)
+
+![image/svg](assets/lightning-logo2.svg)
+
+## Overview
+Lightning-4b is a language model specifically designed and trained for data analysis tasks on local devices. With just a laptop (fully tested on an M4 MacBook Air with 16GB RAM), you can process data without ever sending it to major LLM provider.
+### What it can do
+- Data visualization    
+- Table joins
+- t-tests
+- Unlimited rows, 30+ tables analyzed simultaneously
+### What it cannot do
+- Business reasoning or management decision-making advice
+- Multi-turn analysis
+
+To use this model, install [quelmap](https://github.com/quelmap-inc/quelmap) on your device.  
+Quelmap is an open-source data analysis assistant with every essential features like data upload and an built-in python sandbox.  
+For installation instructions, see the [Quick Start](https://github.com/quelmap-inc/quelmap).
+![image/gif](.assets/preview.gif)
+### Performance
+This model was trained specifically for use with [quelmap](https://github.com/quelmap-inc/quelmap).  
+It was evaluated using a sample database and 122 analysis queries, and achieved performance surpassing models with **50x more parameters**.
+
+For details about the model and its training process, see the [Lightning-4b Details](https://quelmap.com/lightinig-4b) page.
+
+![image/svg](.assets/lightning.svg)
+
+### Running Model on your machine
+You can easily install Lightning-4b and quelmap by following the [Quick Start](https://github.com/quelmap-inc/quelmap).
+
+Lightning-4b has multiple quantization versions depending on your hardware.  
+It runs smoothly on laptops, and on higher-spec machines it can handle more tables (30+ tables) and longer chat histories.
+
+Example Specs and Model Versions
+- Laptop (e.g. mac book air 16GB) - 4bit Quantization + 10,240 Context Window
+```
+ollama pull hf.co/quelmap/Lightning-4b-GGUF-short-ctx:Q4_K_M
+```
+- Gaming Laptop - 4bit Quantization + 40,960 Context Window
+```
+ollama pull hf.co/quelmap/Lightning-4b-GGUF:Q4_K_M
+```
+- Powerful PC with GPU - No Quantization + 40,960 Context Window
+```
+ollama pull hf.co/quelmap/Lightning-4b-GGUF:F16
+```
+
+For more details, please refer to the  [Lightning-4b Details](https://quelmap.com/lightinig-4b) page.

config.json

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+{
+    "model_type": "qwen3"
+}

params

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+{
+    "temperature": 0.2,
+    "min_p" : 0.00,
+    "top_k" : 20,
+    "top_p" : 0.95,
+    "num_ctx" : 40960
+}

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