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---
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)
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