Create README.md

README.md

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+# Model Card for Respeecher/ukrainian-data2vec
+
+This model can be used as Feature Extractor model for Ukrainian language audio data
+
+It can also be used as Backbone for downstream tasks, like ASR, Audio Classification, etc.
+
+### How to Get Started with the Model
+
+```python
+from transformers import AutoProcessor, Data2VecAudioModel
+import torch
+from datasets import load_dataset, Audio
+
+dataset = load_dataset("mozilla-foundation/common_voice_11_0", "uk", split="validation")
+# Resample
+dataset = dataset.cast_column("audio", Audio(sampling_rate=16_000))
+
+processor = AutoProcessor.from_pretrained("Respeecher/ukrainian-data2vec")
+model = Data2VecAudioModel.from_pretrained("Respeecher/ukrainian-data2vec")
+
+# audio file is decoded on the fly
+inputs = processor(dataset[0]["audio"]["array"], sampling_rate=sampling_rate, return_tensors="pt")
+with torch.no_grad():
+    outputs = model(**inputs)
+
+last_hidden_states = outputs.last_hidden_state
+list(last_hidden_states.shape)
+```