| --- |
| 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 |
| - m-a-p/Code-Feedback |
| 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` |
| - ` |
| - `m-a-p/Code-Feedback` |
| - ` |
| - ` |
| - `HuggingFaceH4/llava-instruct-mix-vsft` |
| - |
|
|
| **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` |
