| | --- |
| | base_model: unsloth/Qwen3-8B-Base-unsloth-bnb-4bit |
| | tags: |
| | - transformers |
| | - qwen3 |
| | - Unsloth |
| | - code |
| | - agent |
| | - Fine-tune |
| | license: apache-2.0 |
| | language: |
| | - en |
| | datasets: |
| | - TeichAI/MiniMax-M2.1-Code-SFT |
| | - TeichAI/MiniMax-M2.1-8800x |
| | - TeichAI/convo-v1 |
| | - AlicanKiraz0/Agentic-Chain-of-Thought-Coding-SFT-Dataset-v1.1 |
| | - TeichAI/claude-4.5-opus-high-reasoning-250x |
| | pipeline_tag: text-generation |
| | --- |
| | # LocalCodeViber |
| |
|
| | **LocalCodeViber** is a local-first agentic coding model built on [Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B), fine-tuned for tool-calling, multi-step code generation, and autonomous error recovery. Designed to run entirely on consumer hardware — no API, no cloud, no cost per token. |
| |
|
| | This is the SFT foundation model. Reinforcement learning is ongoing. |
| |
|
| | --- |
| |
|
| | ## What it does |
| |
|
| | LocalCodeViber was trained to operate as a coding agent — not just generate code, but use tools to read files, write files, run commands, search the web, and recover from failures just like a real developer would. |
| |
|
| | It can: |
| |
|
| | - Read and edit files in a workspace |
| | - Write complete, working code from a single prompt |
| | - Execute shell commands and interpret the output |
| | - Recover from failed tool calls without giving up |
| | - Create pull requests on GitHub repositories |
| | - Think through problems step by step using native `<think>` tags before acting |
| |
|
| | --- |
| |
|
| | ## Model Details |
| |
|
| | | | | |
| | |---|---| |
| | | **Base Model** | Qwen3-8B-Base | |
| | | **Architecture** | Qwen3 transformer, 36 layers | |
| |
|
| | ## Training Data |
| |
|
| | LocalCodeViber was trained on a curated mix of 14,837 examples across 5 datasets: |
| |
|
| | | Dataset | Examples | Focus | |
| | |---|---|---| |
| | | [TeichAI/convo-v1](https://huggingface.co/datasets/TeichAI/convo-v1) | 777 | Conversational format, instruction following | |
| | | [AlicanKiraz0/Agentic-Chain-of-Thought-Coding-SFT-Dataset-v1.1](https://huggingface.co/datasets/AlicanKiraz0/Agentic-Chain-of-Thought-Coding-SFT-Dataset-v1.1) | ~3,700 | Agentic reasoning and tool use | |
| | | [TeichAI/MiniMax-M2.1-Code-SFT](https://huggingface.co/datasets/TeichAI/MiniMax-M2.1-Code-SFT) | ~1,300 | Agentic Code generation | |
| | | [TeichAI/MiniMax-M2.1-8800x](https://huggingface.co/datasets/TeichAI/MiniMax-M2.1-8800x) | 8,800 | Diverse coding tasks | |
| | | [TeichAI/claude-4.5-opus-high-reasoning-250x](https://huggingface.co/datasets/TeichAI/claude-4.5-opus-high-reasoning-250x) | 250 | High-quality reasoning traces | |
| |
|
| | The dataset mix emphasises real agentic tool-use patterns including failed tool calls that are identified, diagnosed, and corrected — giving the model genuine error recovery capability rather than just pattern matching on success cases. |
| |
|
| | --- |
| |
|
| | ## Tools |
| |
|
| | LocalCodeViber understands the following tool schema out of the box: |
| |
|
| | ```json |
| | ["read_file", "write_file", "edit_file", "list_directory", "search_code", "run_command", "web_search"] |
| | ``` |
| |
|
| | These match the tools in the training data. Pass them via the standard OpenAI tool calling API. |
| |
|
| | --- |
| |
|
| | ## Usage |
| |
|
| | ### LM Studio (Recommended) |
| |
|
| | 1. Download the GGUF version: [Bob-the-Koala/LocalCodeViber-GGUF](https://huggingface.co/Bob-the-Koala/LocalCodeViber-GGUF) |
| | 2. Load in LM Studio and break free from API costs! |
| |
|
| | ### Ollama |
| |
|
| | ```bash |
| | ollama run hf.co/Bob-the-Koala/LocalCodeViber-GGUF:Q4_K_M |
| | ``` |
| |
|
| | ### Transformers |
| |
|
| | ```python |
| | from transformers import AutoModelForCausalLM, AutoTokenizer |
| | |
| | model = AutoModelForCausalLM.from_pretrained( |
| | "Bob-the-Koala/LocalCodeViber", |
| | torch_dtype="auto", |
| | device_map="auto" |
| | ) |
| | tokenizer = AutoTokenizer.from_pretrained("Bob-the-Koala/LocalCodeViber") |
| | ``` |
| |
|
| | --- |
| |
|
| | ## GGUF Versions |
| |
|
| | Available in [Bob-the-Koala/LocalCodeViber-GGUF](https://huggingface.co/Bob-the-Koala/LocalCodeViber-GGUF): |
| |
|
| | | Quantization | Size | Use case | |
| | |---|---|---| |
| | | `Q4_K_M` | ~4.8 GB | Everyday use, best balance | |
| |
|
| | --- |
| |
|
| | ## System Prompt |
| |
|
| | For best results, use this system prompt: |
| |
|
| | ``` |
| | You are a helpful coding assistant with access to file operations and code analysis tools. |
| | Complete the user's task thoroughly and efficiently. |
| | When given a coding task, create working code files in the workspace. |
| | ``` |
| |
|
| | --- |
| |
|
| | ## Limitations |
| |
|
| | - Base model started from bnb-4bit weights — quality ceiling is below a full precision 8B model |
| | - SFT only — reinforcement learning is in progress and will significantly improve reasoning quality |
| | - Not suitable for tasks requiring knowledge past Qwen3's training cutoff |
| |
|
| | --- |
| |
|
| | ## Roadmap |
| |
|
| | - [ ] **LocalCodeViber-RL** — reinforcement learning on top of this SFT base, optimising for code correctness and task completion |
| | - [ ] **LocalCodeViber-Claw** — fine-tuned specifically for [OpenClaw](https://github.com/openclaw/openclaw) skill schemas, channel routing, extra safety, and memory system |
| | - [ ] **LocalCodeViber-14B** — same training recipe on Qwen3-14B for substantially higher capability |
| |
|
| | --- |
| |
|
| | ## Acknowledgements |
| |
|
| | LocalCodeViber was trained using [Unsloth](https://github.com/unslothai/unsloth) and would not exist without the datasets provided by [TeichAI](https://huggingface.co/TeichAI) and [AlicanKiraz0](https://huggingface.co/AlicanKiraz0). |
| |
|
| | --- |
| |
|
| | ## License |
| |
|
| | This model is released under the Apache 2.0 license |
| |
|
| | --- |
| |
|
| | *Built by [Bob-the-Koala](https://huggingface.co/Bob-the-Koala)* |
| | [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
