---
license: other
base_model:
  - Qwen/Qwen3.5-4B
library_name: llama.cpp
tags:
  - gguf
  - qwen
  - qwen3.5
  - code
  - coder
  - conversational
  - text-generation
  - withinusai
language:
  - en
datasets:
  - WithinUsAI/Python_GOD_Coder_50k
  - reedmayhew/gemini-3.1-pro-2048-reasoning-1100x
  - m-a-p/Code-Feedback
  - crownelius/Opus-4.6-Reasoning-2100x-formatted
  - crownelius/Opus4.6-No-Reasoning-260x
  - crownelius/Creative_Writing_Multiturn_Enhanced
  - HuggingFaceH4/llava-instruct-mix-vsft
  - Roman1111111/gemini-3-pro-10000x-hard-high-reasoning
model_type: gguf
inference: false
---

# WithIn-Us-Coder-4B.gguf

**WithIn-Us-Coder-4B.gguf** is a GGUF release from **WithIn Us AI**, built for local inference and coding-focused assistant use cases. It is based on **Qwen/Qwen3.5-4B** and distributed in quantized GGUF formats for efficient deployment in llama.cpp-compatible runtimes.

## Model Summary

This model is intended as a coding-oriented conversational assistant with emphasis on:

- code generation
- code reasoning
- implementation planning
- debugging assistance
- instruction following
- general assistant-style chat for development workflows

This repository currently provides the following GGUF variants:

- `WithIn-Us-Coder-4B.Q4_K_M.gguf`
- `WithIn-Us-Coder-4B.Q5_K_M.gguf`

## Creator

**WithIn Us AI** is the creator of this model release, including the model packaging, fine-tuning / merging concept, process, naming, and GGUF distribution.

## Base Model

This model is based on:

- **Qwen/Qwen3.5-4B**

Credit and appreciation go to the original creators of the base LLM architecture and weights.

## Training Data

The current repository metadata lists the following datasets as part of the model’s training / fine-tuning lineage:

- `WithinUsAI/Python_GOD_Coder_50k`
- `reedmayhew/gemini-3.1-pro-2048-reasoning-1100x`
- `m-a-p/Code-Feedback`
- `crownelius/Opus-4.6-Reasoning-2100x-formatted`
- `crownelius/Opus4.6-No-Reasoning-260x`
- `crownelius/Creative_Writing_Multiturn_Enhanced`
- `HuggingFaceH4/llava-instruct-mix-vsft`
- `Roman1111111/gemini-3-pro-10000x-hard-high-reasoning`

**Attribution note:**  
WithIn Us AI does not claim ownership over third-party base models or third-party datasets. Full credit, thanks, and attribution belong to the original model and dataset creators.

## Intended Use

This model is intended for:

- local coding assistants
- offline development help
- code explanation
- bug-fixing support
- prompt-based code generation
- experimentation in llama.cpp and GGUF-compatible environments

### Suggested Use Cases

- generating Python, JavaScript, C++, and other programming language snippets
- explaining code blocks
- rewriting or improving functions
- brainstorming implementation strategies
- creating scaffolding and prototypes
- assisting with debugging and refactoring

## Out-of-Scope Use

This model is not guaranteed to be reliable for:

- high-stakes legal advice
- medical advice
- financial decision-making
- autonomous execution without review
- security-critical production decisions without human verification

Users should always validate generated code before deployment.

## Quantization Formats

This repository currently includes:

- **Q4_K_M** for smaller memory footprint and faster local inference
- **Q5_K_M** for improved quality while remaining efficient

Choose the quant level based on your hardware budget and quality needs.

## Prompting Notes

As a coding-focused conversational model, best results usually come from prompts that are:

- specific
- structured
- explicit about language, framework, or goal
- clear about desired output format

Example prompt style:

> Write a Python function that parses a CSV file, removes duplicate rows by email, and saves the cleaned result. Include error handling and comments.

## Limitations

Like other language models, this model may:

- hallucinate APIs or library behavior
- generate insecure or inefficient code
- make reasoning mistakes
- produce outdated patterns
- require prompt iteration for best results

Human review is strongly recommended, especially for production code.

## License

This repository uses a **custom WithIn Us AI license approach**.

- The base model may be subject to its original upstream license and terms.
- Third-party datasets remain the property of their respective creators / licensors.
- WithIn Us AI claims authorship of the fine-tuning / merging concept, process, packaging, naming, and release structure for this model distribution.
- This repository does **not** claim ownership over third-party datasets or the underlying upstream base model.

You can include a `LICENSE` file in this repository with the exact custom terms you want enforced.

## Acknowledgments

Special thanks to:

- **Qwen** for the base model
- all third-party dataset creators listed above
- the open-source GGUF / llama.cpp ecosystem
- the broader Hugging Face community

## Files

Current repository files include:

- `WithIn-Us-Coder-4B.Q4_K_M.gguf`
- `WithIn-Us-Coder-4B.Q5_K_M.gguf`

## Disclaimer

This model may generate incorrect, biased, insecure, or incomplete outputs.  
Use responsibly, validate important results, and review all generated code before real-world use.