Create README.md

README.md

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+## Usage
+The model can be used directly (without a language model) as follows:
+```python
+import soundfile as sf
+import torch
+from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
+import argparse
+def parse_transcription(wav_file):
+    # load pretrained model
+    processor = Wav2Vec2Processor.from_pretrained("addy88/wav2vec2-nepali-stt")
+    model = Wav2Vec2ForCTC.from_pretrained("addy88/wav2vec2-nepali-stt")
+    # load audio
+    audio_input, sample_rate = sf.read(wav_file)
+    # pad input values and return pt tensor
+    input_values = processor(audio_input, sampling_rate=sample_rate, return_tensors="pt").input_values
+    # INFERENCE
+    # retrieve logits & take argmax
+    logits = model(input_values).logits
+    predicted_ids = torch.argmax(logits, dim=-1)
+    # transcribe
+    transcription = processor.decode(predicted_ids[0], skip_special_tokens=True)
+    print(transcription)
+```