README.md

---
license: apache-2.0
tags:
- whisper
- fine-tuned
- malay
- speech-to-text
datasets:
- custom-dataset
model-index:
- name: whisper-RMTfinetuned
  results:
  - task:
      type: automatic-speech-recognition
    dataset:
      name: Malay Audio Datasets
      type: custom
    metrics:
    - type: wer
      value: 5.6
---

# Whisper-RMTfinetuned

This model is a fine-tuned version of OpenAI's Whisper model for **Malay speech-to-text transcription**.

## **Model Description**
- **Base Model**: OpenAI Whisper-Small
- **Fine-Tuned on**: Malay language dataset
- **Intended Use**: Speech recognition for Malay audio

## **Usage**
```python
from transformers import WhisperProcessor, WhisperForConditionalGeneration
import torch

model = WhisperForConditionalGeneration.from_pretrained("rmtariq/whisper-RMTfinetuned")
processor = WhisperProcessor.from_pretrained("rmtariq/whisper-RMTfinetuned")

audio = "/path/to/audio.wav"
input_features = processor(audio, sampling_rate=16000, return_tensors="pt").input_features

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

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