Agent Gemma 4 E4B Frontend
is a domain-adapted version of the
google/gemma-4-E4B-it
model, specifically fine-tuned for front-end engineering. It is designed to be a "specialist" in React, Vue, Tailwind CSS, and modern JavaScript/TypeScript development while maintaining general reasoning and tool-use capabilities.
The "E" in E4B denotes "Effective" parameters—while the model has 8B total parameters, only 4.5B are active during the forward pass, optimized for high intelligence-per-parameter and edge-device efficiency.
Training Details
Base Model:
google/gemma-4-E4B-it
Architecture:
4.5B Effective / 8B Total parameters.
Optimization:
QLoRA (4-bit quantization with NormalFloat4, rank 16, alpha 32).
Framework:
Unsloth for accelerated training.
Context Window:
128,000 tokens (trained with 2,048 max sequence length, packed).
Compute:
NVIDIA A100-SXM4-80GB.
Data Mixture
The training follows a strategic 67.7% / 32.3% split to optimize domain expertise while preventing catastrophic forgetting:
67.7% Front-End Specialization:
High-aesthetic Next.js/Tailwind components.
Rigorous React/TypeScript instructions.
Modern UI library integration (Shadcn UI, etc.).
32.3% Regularization & Core Competency:
Multi-turn tool-use and reasoning traces.
Structured JSON and API interaction.
General conversational fluidity.
Intended Use
This model is intended for:
Production-ready code generation for React, Vue, and Tailwind CSS.
Multi-step reasoning for complex front-end architectural tasks.
Agentic workflows involving tool-use and terminal interactions.
GGUF Compatibility
This repository provides a
q4_k_m
GGUF version compatible with:
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