---
license: other
license_name: mixed-apache-2.0-mit-and-openmdw-1.1
license_link: LICENSE
tags:
- penra
- litert
- on-device
- handwriting-recognition
- speech-recognition
---

# Penra offline models

The model files the [Penra](https://play.google.com/store/apps/details?id=com.penra.app) note app downloads to
read handwriting, write speech and search notes **on the device, with no server**. They are repackaged or converted
from the open models below; the app picks one reading bundle by the phone's memory.

| File | What it is | Made from | License |
|---|---|---|---|
| `penra-ocr-1120.litertlm` | Handwriting reading and speech, phones with 8 GB memory | Gemma 4 E4B, LiteRT-LM bundle with a 1120-token vision signature, trimmed vocabulary | Apache 2.0 (Gemma 4) |
| `penra-ocr-560.litertlm` | The same, faster on phones with a slow GPU (560-token vision signature, MTP drafter for speculative decoding) | Gemma 4 E4B | Apache 2.0 (Gemma 4) |
| `penra-e2b-1120.litertlm` | The same for phones with less memory | Gemma 4 E2B | Apache 2.0 (Gemma 4) |
| `embeddinggemma-2-text-270m.litertlm` | Finding notes by meaning | EmbeddingGemma 2 | Apache 2.0 |
| `uvdoc.onnx` | Flattening a photographed page before reading | UVDoc (PaddlePaddle) | Apache 2.0 |
| `whisper_tr_enc30_dwi4.tflite` | Speech to text, high accuracy (all 15 languages): audio encoder, 30-s window, int4 weights | OpenAI Whisper large-v3-turbo + Penra Turkish LoRA (merged) | MIT (Whisper) |
| `whisper_tr_dec30_kv_mixd.tflite` | The same: text decoder with KV cache, mixed precision | OpenAI Whisper large-v3-turbo + Penra Turkish LoRA (merged) | MIT (Whisper) |
| `whisper_tr_tokenizer.json` | The same: tokenizer | OpenAI Whisper large-v3-turbo | MIT (Whisper) |
| `eg2_tr_fc8.tflite` | Faster Turkish speech to text (Pro): EmbeddingGemma 2 encoder + CTC reader, int8 | EmbeddingGemma 2 | Apache 2.0 |
| `eg2_tr_3gram_spoken.bin`, `eg2_tr_unigrams.txt` | The same: spoken-Turkish 3-gram language model and its word list | Penra (own corpus) | Apache 2.0 |
| `nemotron-asr-step-dwi8.tflite` | Live text while recording: streaming encoder step, int8 | NVIDIA Nemotron 3.5 ASR Streaming 0.6B | OpenMDW 1.1 |
| `nemotron-decoder.tflite` | Live text while recording: RNN-T prediction network and joint | NVIDIA Nemotron 3.5 ASR Streaming 0.6B | OpenMDW 1.1 |
| `nemotron-3-diarization-q8_0.gguf` | Who spoke when (planned) | NVIDIA Nemotron 3 Diarization | OpenMDW 1.1 |
| `wordlists/<lang>/<lang>_50k.txt` | Word lists for the reading check | FrequencyWords (Hermit Dave), commit 525f9b5 | CC BY-SA 4.0 |

`manifest.json` lists every file with its size and SHA-256; the app checks both before using a file.

## Licenses

- Gemma 4 and EmbeddingGemma 2: Apache License 2.0 ([Gemma 4 license](https://ai.google.dev/gemma/docs/gemma_4_license)).
- NVIDIA Nemotron 3.5 ASR Streaming and Nemotron 3 Diarization: [OpenMDW License 1.1](https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b).
- OpenAI Whisper large-v3-turbo: MIT License ([model card](https://huggingface.co/openai/whisper-large-v3-turbo)).
- UVDoc: Apache License 2.0.
- FrequencyWords word lists: CC BY-SA 4.0, by Hermit Dave.

These files are modified forms of the original models (format conversion, quantization, repackaging); they are
provided as is, without warranty.