maqsudxo1ja/uz-whisper-small-stt

Uzbek Whisper Small STT

This repository contains a Whisper Small speech-to-text model prepared for Hugging Face upload. The model is based on openai/whisper-small and is configured to transcribe Uzbek by default.

The model files are ready to use with the transformers automatic speech recognition pipeline.

Model Details

• Model type: Whisper Small / Automatic Speech Recognition
• Default task: transcription
• Default language: Uzbek (uz)
• Supported languages in tokenizer/config: Uzbek, English, Russian, and other Whisper multilingual tokens
• Base model: openai/whisper-small
• Format: safetensors
• License: Apache-2.0

Usage

Replace YOUR_USERNAME/uz-whisper-small-stt with your Hugging Face repository name after upload.

from transformers import pipeline

asr = pipeline(
    "automatic-speech-recognition",
    model="YOUR_USERNAME/uz-whisper-small-stt",
)

result = asr("audio.wav")
print(result["text"])

For direct generation:

import torch
import torchaudio
from transformers import WhisperForConditionalGeneration, WhisperProcessor

model_id = "YOUR_USERNAME/uz-whisper-small-stt"

processor = WhisperProcessor.from_pretrained(model_id)
model = WhisperForConditionalGeneration.from_pretrained(model_id)

audio, sr = torchaudio.load("audio.wav")
if audio.shape[0] > 1:
    audio = audio.mean(dim=0, keepdim=True)

inputs = processor(
    audio.squeeze().numpy(),
    sampling_rate=sr,
    return_tensors="pt",
)

with torch.no_grad():
    predicted_ids = model.generate(inputs.input_features)

text = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
print(text)

Evaluation

No verified benchmark results are included in this prepared upload package. Add WER/CER numbers here only after testing on your own evaluation set.

Upload

Install the Hugging Face CLI and login:

pip install -U "huggingface_hub[cli]"
huggingface-cli login

Create a repository on Hugging Face, then upload this folder:

huggingface-cli upload YOUR_USERNAME/uz-whisper-small-stt . --repo-type model

Run the upload command from inside this folder:

cd hf_ready_model