Create README.md

README.md

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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  # (Replace with actual WER score)
+---
+
+# 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)