Update README.md

README.md

@@ -11,6 +11,9 @@ tags:
 - speech
 - xlsr-fine-tuning-week
 license: apache-2.0
+widget:
+- example_title: test sound with Russian speech
+  src: https://huggingface.co/bond005/wav2vec2-large-ru-golos/blob/main/test_sound_ru.wav
 model-index:
 - name: XLSR Wav2Vec2 Russian by Ivan Bondarenko
   results:
@@ -50,6 +53,33 @@ The Wav2Vec2 model is based on [facebook/wav2vec2-large-xlsr-53](https://hugging
 
 When using this model, make sure that your speech input is sampled at 16kHz.
 
+## Usage
+
+To transcribe audio files the model can be used as a standalone acoustic model as follows:
+
+```python
+ from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC
+ from datasets import load_dataset
+ import torch
+ 
+ # load model and tokenizer
+ processor = Wav2Vec2Processor.from_pretrained("bond005/wav2vec2-large-ru-golos")
+ model = Wav2Vec2ForCTC.from_pretrained("bond005/wav2vec2-large-ru-golos")
+     
+ # load dummy dataset and read soundfiles
+ ds = load_dataset("bond005/sberdevices_golos_10h_crowd", split="test")
+ 
+ # tokenize
+ processed = processor(ds[0]["audio"]["array"], return_tensors="pt", padding="longest")  # Batch size 1
+ 
+ # retrieve logits
+ logits = model(processed.input_values, attention_mask=processed.attention_mask).logits
+ 
+ # take argmax and decode
+ predicted_ids = torch.argmax(logits, dim=-1)
+ transcription = processor.batch_decode(predicted_ids)
+ ```
+
 ## Citation
 If you want to cite this model you can use this: