Instructions to use DummyTesty/gemmaspark-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use DummyTesty/gemmaspark-model with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 1,277 Bytes
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base_model: litert-community/gemma-4-E2B-it-litert-lm
language:
- en
- hi
- ta
- te
- bn
- mr
- gu
- kn
- ml
- or
- pa
- ur
license: gemma
tags:
- gemma
- litert
- android
- on-device
- offline
- education
---
# Gemma 4 E2B — LiteRT-LM (EdSparkAI)
INT4-quantized `.litertlm` model file used by **EdSparkAI**, a fully offline Android AI tutor.
Based on [litert-community/gemma-4-E2B-it-litert-lm](https://huggingface.co/litert-community/gemma-4-E2B-it-litert-lm).
## File
| | |
|---|---|
| **Filename** | `model.litertlm` |
| **Format** | LiteRT-LM (MediaPipe) |
| **Quantization** | INT4 |
| **Size** | ~2.4 GB |
## Usage
This model runs on Android via **MediaPipe LiteRT 0.10.14** on the CPU backend. Used in [EdSparkAI](https://github.com/Destroyer1543/EdSparkAI) — an offline bilingual classroom assistant that explains textbook pages in 12 Indian languages.
```kotlin
val cfg = EngineConfig(
modelPath = "/path/to/model.litertlm",
backend = Backend.CPU(),
maxNumTokens = 2048,
)
val engine = Engine(cfg)
engine.initialize()
```
### Device requirements
- Android 8.0+ (API 26+)
- 4 GB RAM minimum
- 3 GB free storage
## License
Gemma is a trademark of Google LLC. Use is subject to the [Gemma Terms of Use](https://ai.google.dev/gemma/terms).
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