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gemma-3n-E2B-it-Q6_K
sunil-pathak/gemma-3n-E2B-it-Q6_K
gemma-3n-E2B-it-Q6_K is a text generation model from sunil-pathak. Use it when you need the model to write or continue text. The card lists the license as other.
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.gguf3.7 GB · 100%
At a glance
- Task
- Text Generation
- License
- other
- Access
- Public
- Created
- Apr 18, 2026
- Updated
- Apr 19, 2026
- SHA
- 0d0ba7b9
Try a prompt
Model card
From the Hugging Face model README
gemma-3n-E2B-it — GGUF (Q6_K)
📊 Performance Metrics
- Hardware: Intel(R) Xeon(R) CPU @ 2.20GHz (4 vCPUs)
- Size: 3.47 GB
- Speed (Generation): 5.41 tokens/sec
- Speed (Prompt): 10.76 tokens/sec
- KV Cache Usage: 0.0143 GB
- Quantization: Q6_K
🔷 Model Overview
This repository contains a GGUF quantized version of:
- Base Model: gemma-3n-E2B-it
- Format: GGUF (optimized for llama.cpp inference)
- Precision: Q6_K
- Efficiency Score: 1.5603 (TPS/GB)
GGUF format provides:
- Fast loading via memory mapping
- Single-file model distribution
- Cross-platform compatibility
- Efficient inference with llama.cpp
📦 Files
| File | Description |
|---|---|
gemma-3n-E2B-it-Q6_K.gguf | Quantized GGUF model file |
⚙️ Technical Details
| Parameter | Value |
|---|---|
| Architecture | gemma-3n-E2B-it |
| Format | GGUF |
| Precision | Q6_K |
| Runtime | llama.cpp |
| Benchmark Hardware | Intel(R) Xeon(R) CPU @ 2.20GHz (4 vCPUs) |
| Context Latency | 29.69s |
| Memory (KV) | 0.0143 GB |
⚡ Why GGUF?
GGUF is designed for efficient inference:
- Optimized for llama.cpp
- Supports CPU and GPU inference
- Single-file deployment
- Memory-mapped loading for speed
- Ideal for edge / local environments
⚠️ License & Usage
This is a converted derivative model.
- You must comply with the original model license of gemma-3n-E2B-it
- This is not an official release
- No additional rights are granted
- Original ownership remains with the base model creator
🚀 Quick Start (llama.cpp)
./llama-cli -m gemma-3n-E2B-it-Q6_K.gguf -p "Explain AI simply"
- Task
- Text Generation
- License
- other
- Created
- Apr 18, 2026
- Updated
- Apr 19, 2026