Update README.md

README.md

@@ -8,6 +8,12 @@ metrics:
 model-index:
 - name: whisper-medium-myanmar
   results: []
+datasets:
+- chuuhtetnaing/myanmar-speech-dataset-openslr-80
+language:
+- my
+pipeline_tag: automatic-speech-recognition
+library_name: transformers
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,24 +21,28 @@ should probably proofread and complete it, then remove this comment. -->
 
 # whisper-medium-myanmar
 
-This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the [chuuhtetnaing/myanmar-speech-dataset-openslr-80](https://huggingface.co/datasets/chuuhtetnaing/myanmar-speech-dataset-openslr-80) dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.2282
 - Wer: 49.4657
 
-## Model description
+## Usage
 
-More information needed
+```python
+from datasets import Audio, load_dataset
+from transformers import pipeline
 
-## Intended uses & limitations
+# Load a sample audio
+dataset = load_dataset("chuuhtetnaing/myanmar-speech-dataset-openslr-80")
+dataset = dataset.cast_column("audio", Audio(sampling_rate=16000))
+test_dataset = dataset['test']
+input_speech = test_dataset[42]['audio']
 
-More information needed
+pipe = pipeline(model='chuuhtetnaing/whisper-large-v3-myanmar')
 
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
+output = pipe(input_speech, generate_kwargs={"language": "myanmar", "task": "transcribe"})
+print(output['text']) # ကျမ ပြည်ပ မှာ ပညာသင် တော့ စာမေးပွဲ ကို တပတ်တခါ စစ်တယ်
+```
 
 ### Training hyperparameters
 
@@ -108,4 +118,4 @@ The following hyperparameters were used during training:
 - Transformers 4.35.2
 - Pytorch 2.1.1+cu121
 - Datasets 2.14.5
-- Tokenizers 0.15.1
+- Tokenizers 0.15.1