---
license: cc-by-sa-4.0
base_model: oruk/orukeet
base_model_relation: quantized
pipeline_tag: automatic-speech-recognition
library_name: whisper.cpp
tags:
  - ggml
  - gguf
  - whisper.cpp
  - automatic-speech-recognition
  - on-device
  - quantized
  - parakeet
---

# orukeet-ggml

GGML conversion of **oruk/orukeet** (.nemo) for the Parakeet TDT engine that ships inside whisper.cpp ≥ 1.9, in f16 plus q8_0 / q5_0 / q4_0.

**Source checkpoint:** [oruk/orukeet](https://huggingface.co/oruk/orukeet) by oruk (fine-tune of NVIDIA Parakeet TDT 0.6B v3) · **License:** cc-by-sa-4.0 (unchanged; this repo only re-packages the weights)
**Engine:** Load with [whisper.cpp](https://github.com/ggml-org/whisper.cpp) ≥ 1.9 `parakeet-cli -m <file>` (the Parakeet TDT engine that ships inside whisper.cpp). Not compatible with mudler/parakeet.cpp GGUF files.

## Files

| File | Quantization | Size | Note |
|---|---|---|---|
| `ggml-orukeet-f16.bin` | f16 | 1256 MB |  |
| `ggml-orukeet-q4_0.bin` | q4_0 | 356 MB |  |
| `ggml-orukeet-q5_0.bin` | q5_0 | 434 MB |  |
| `ggml-orukeet-q8_0.bin` | q8_0 | 669 MB |  |

`f16` is the lossless conversion; `q8_0` is nearly identical in accuracy at ~55 % of the size; `q5_0`/`q5_k` are the phone-friendly choice; `q4_*` is smallest with a small accuracy cost.

## How these were made

Converted from the upstream checkpoint with the engine's own converter, then quantized with the engine's quantizer. Each variant was checked by transcribing short Portuguese and English samples before upload.

## Attribution

Weights are derivative works of the upstream model and keep its license. Please cite the original authors (oruk (fine-tune of NVIDIA Parakeet TDT 0.6B v3)). The conversion and hosting here are maintained by [JoaoZaokk](https://huggingface.co/JoaoZaokk) so that the download links used by the Odysseus / Open WebUI native apps stay stable. No warranty.