Update README.md

README.md

@@ -1,3 +1,25 @@
 ---
 license: mit
 ---
+
+The model was fine-tuned on 300h of public and private speech data. More information will be given once the underlying paper gets published.
+
+```
+import librosa
+from transformers import Wav2Vec2Processor, AutoModelForCTC
+import torch
+
+audio, _ = librosa.load("[audio_path]", sr=16000)
+model = AutoModelForCTC.from_pretrained("racai/wav2vec2-base-100k-voxpopuli-romanian")
+processor = Wav2Vec2Processor.from_pretrained("racai/wav2vec2-base-100k-voxpopuli-romanian")
+
+input_dict = processor(audio, sampling_rate=16000, return_tensors="pt")
+
+with torch.inference_mode():
+    logits = model(input_dict.input_values).logits
+
+predicted_ids = torch.argmax(logits, dim=-1)
+predicted_sentence = processor.batch_decode(predicted_ids)[0]
+
+print("Prediction:", predicted_sentence)
+```