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wefamm/aiAI_coder_V1.4B

sourceHugging Faceotherupdated 1mo agoView on Hugging Face
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basemodel: Qwen/Qwen3.5-4B libraryname: transformers license: apache-2.0 language:

  • —en pipeline_tag: text-generation tags:
  • —qwen3.5
  • —coding
  • —reasoning
  • —lora
  • —sft
  • —agentic
  • —python
  • —javascript
  • —sql basemodelrelation: finetune ---

THE MUCH IMPROVED V2 IS NOW RELEASE @ wefamm/aiAIcoderV2_4B

aiAIcoderV1.4B

4B parameters • Fine-tuned for coding & agentic tasks • <1 hour training

🤗 Model | 📊 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