Update README.md

README.md

@@ -31,9 +31,44 @@ For more information, please refer to Section *5.1.2* of the [official XLS-R pap
 
 ## Usage
 
-TODO...
+As this a standard sequence to sequence transformer model, you can use the `generate` method to generate the
+transcripts by passing the speech features to the model.
+
+You can use the model directly via the ASR pipeline
+
+```python
+from datasets import load_dataset
+from transformers import pipeline
+
+# replace following lines to load an audio file of your choice
+librispeech_en = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation")
+audio_file = librispeech_en[0]["file"]
+
+asr = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-xls-r-300m-21-to-en", feature_extractor="facebook/wav2vec2-xls-r-300m-21-to-en")
+
+translation = asr(audio_file)
+```
+
+or step-by-step as follows:
+
+```python
+import torch
+from transformers import Speech2Text2Processor, SpeechEncoderDecoder
+from datasets import load_dataset
+
+model = SpeechEncoderDecoder.from_pretrained("facebook/wav2vec2-xls-r-300m-21-to-en")
+processor = Speech2Text2Processor.from_pretrained("facebook/wav2vec2-xls-r-300m-21-to-en")
+
+ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation")
+
+inputs = processor(ds[0]["audio"]["array"], sampling_rate=16_000, return_tensors="pt")
+generated_ids = model.generate(input_ids=inputs["input_features"], attention_mask=inputs["attention_mask"])
+transcription = processor.batch_decode(generated_ids)
+```
 
 ## Results `{lang}` -> `en`
 
+See the row of **XLS-R (0.3B)** for the performance on [Covost2](https://huggingface.co/datasets/covost2) for this model.
+
 ![results image](https://raw.githubusercontent.com/patrickvonplaten/scientific_images/master/X-%3EEnglish.png)