Faster-Whisper (CTranslate2) Version of Nepali Whisper Medium
This repository contains the Int8 Quantized version of the State-of-the-Art Nepali ASR model Dragneel/whisper-medium-nepali-openslr.
It is optimized for high-speed inference on CPUs and GPUs using the faster-whisper or ctranslate2 libraries.
Performance
- WER: 11.17% (OpenSLR Test Set)
- Speed: ~4x faster than the original FP16 model.
- Memory: Requires < 2GB RAM.
Usage
Install the library:
pip install faster-whisperRun inference:
from faster_whisper import WhisperModel # Load model directly from Hugging Face model = WhisperModel("Dragneel/whisper-medium-nepali-openslr-ct2", device="cpu", compute_type="int8") segments, info = model.transcribe("audio.mp3", beam_size=5) for segment in segments: print(segment.text)
This research was supported by the High Performance Computing (HPC) facility at Tribhuvan University, Nepal. We acknowledge the Supercomputer Centre for providing the computational resources required for this wor
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Model tree for Dragneel/whisper-medium-nepali-openslr-ct2
Base model
openai/whisper-medium Finetuned
Dragneel/whisper-medium-nepali-openslr