| --- |
| library_name: peft |
| license: other |
| base_model: Qwen/Qwen3.5-4B-Thinking |
| tags: |
| - base_model:adapter:/root/autodl-tmp/Qwen3.5-4B-Thinking |
| - llama-factory |
| - lora |
| - transformers |
| pipeline_tag: text-generation |
| model-index: |
| - name: aiAIL_coding_V1 |
| results: [] |
| --- |
| |
| --- |
| base_model: Qwen/Qwen3.5-4B |
| library_name: transformers |
| license: apache-2.0 |
| language: |
| - en |
| pipeline_tag: text-generation |
| tags: |
| - qwen3.5 |
| - coding |
| - reasoning |
| - lora |
| - sft |
| - agentic |
| - python |
| - javascript |
| - sql |
| base_model_relation: finetune |
| --- |
| |
| # THE MUCH IMPROVED V2 IS NOW RELEASE @ wefamm/aiAI_coder_V2_4B |
|
|
| # aiAI_coder_V1.4B |
|
|
|
|
| **4B parameters • Fine-tuned for coding & agentic tasks • <1 hour training** |
|
|
| [🤗 Model](https://huggingface.co/aiAI_coder_V1.4B) | [📊 Evaluation](#evaluation) |
|
|
| ## Model Overview |
|
|
| `aiAI_coder_V1.4B` is a specialized coding and agentic assistant fine-tuned from Qwen/Qwen3.5-4B. It is designed to excel in: |
|
|
| - **Multi-language Code Generation**: Python, JavaScript, TypeScript, and SQL |
| - **Reasoning & Problem-Solving**: Step-by-step thinking with `<think>` tag support |
| - **Agentic Workflows**: Tool calling, multi-turn interactions, and task completion |
| - **Instruction Adherence**: Following complex, constrained prompts with high accuracy |
| - **Cost Efficiency**: Optimized for low-latency inference on consumer hardware |
|
|
| This model was distilled from high-quality Grok 4.6 completions and trained with a highly efficient Supervised Fine-Tuning (SFT) recipe, achieving strong coding benchmark performance at a fraction of the cost of larger models [citation:1][citation:7]. |
|
|
| ## Model Details |
|
|
| ### Model Description |
|
|
| `aiAI_coder_V1.4B` is an instruction-tuned language model optimized for code synthesis, debugging, and agentic assistance. It supports: |
|
|
| - Fast, deterministic responses for coding tasks |
| - Accurate code generation in Python, JavaScript, TypeScript, and SQL |
| - Multi-turn reasoning with explicit thinking separation (`<think>...</think>`) |
| - Native support for tool calling and structured outputs |
|
|
| The model can be used as a lightweight, cost-effective alternative to frontier models in many developer workflows. |
|
|
| - **Developed by:** [aiAI] |
| - **Funded by:** [nitrous-0xide (owner & founder)] |
| - **Model type:** Text-generation / Instruction-following |
| - **Language(s):** English |
| - **License:** Apache-2.0 |
| - **Finetuned from:** Qwen/Qwen3.5-4B [citation:1][citation:10] |
|
|
| Uses |
|
|
| ### Direct Use |
|
|
| The model can be used as-is for: |
|
|
| - Interactive coding assistants and chatbots |
| - Code completion and debugging in IDEs |
| - Generating unit tests and documentation |
| - SQL query generation and optimization |
| - Agentic workflows requiring planning and tool use [citation:1] |
|
|
| ### Out-of-Scope Use |
|
|
| - Generating malicious code or content that violates applicable laws |
| - Real-time decision-making in safety-critical systems |
| - Any use that violates the Apache-2.0 license |
|
|
| ## Bias, Risks, and Limitations |
|
|
| - **Hallucination**: May occasionally produce plausible but incorrect code or explanations |
| - **Security**: Generated code should be reviewed for security vulnerabilities |
| - **Context Window**: While optimized for 262K context, performance may degrade at extreme lengths [citation:7] |
| - **Language Coverage**: Primarily trained on English data; performance on other languages is limited |
|
|
| ### Recommendations |
|
|
| - Human-in-the-loop review of generated code before deployment |
| - Use explicit safety filters for disallowed content |
| - Test outputs in sandboxed environments when executing generated code |
|
|
|
|
