gemma-3n-E2B-it-gguf

Name: gemma-3n-E2B-it-gguf
Author: mmnga

161

2.0B

2 languages

—

mmnga

Language Model

OTHER

2B params

New

161 downloads

Early-stage

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Edge AI:

Mobile

Laptop

Server

5GB+ RAM

Mobile

Laptop

Server

Quick Summary

AI model with specialized capabilities.

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

2GB+ RAM

Training Data Analysis

🟡 Average (4.3/10)

Researched training datasets used by gemma-3n-E2B-it-gguf with quality assessment

Specialized For

general

science

multilingual

reasoning

Training Datasets (3)

common crawl

🔴 2.5/10

general

science

Key Strengths

•Scale and Accessibility: At 9.5+ petabytes, Common Crawl provides unprecedented scale for training d...
•Diversity: The dataset captures billions of web pages across multiple domains and content types, ena...
•Comprehensive Coverage: Despite limitations, Common Crawl attempts to represent the broader web acro...

Considerations

•Biased Coverage: The crawling process prioritizes frequently linked domains, making content from dig...
•Large-Scale Problematic Content: Contains significant amounts of hate speech, pornography, violent c...

wikipedia

🟡 5/10

science

multilingual

Key Strengths

•High-Quality Content: Wikipedia articles are subject to community review, fact-checking, and citatio...
•Multilingual Coverage: Available in 300+ languages, enabling training of models that understand and ...
•Structured Knowledge: Articles follow consistent formatting with clear sections, allowing models to ...

Considerations

•Language Inequality: Low-resource language editions have significantly lower quality, fewer articles...
•Biased Coverage: Reflects biases in contributor demographics; topics related to Western culture and ...

arxiv

🟡 5.5/10

science

reasoning

Key Strengths

•Scientific Authority: Peer-reviewed content from established repository
•Domain-Specific: Specialized vocabulary and concepts
•Mathematical Content: Includes complex equations and notation

Considerations

•Specialized: Primarily technical and mathematical content
•English-Heavy: Predominantly English-language papers

Explore our comprehensive training dataset analysis

View All Datasets

Code Examples

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

Usagetextllama.cpp

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build -DGGML_CUDA=ON
cmake --build build --config Release
build/bin/llama-cli -m 'gemma-3n-E2B-it-gguf' -n 128 -c 128 -p 'あなたはプロの料理人です。レシピを教えて' -cnv

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