Update README.md

README.md

@@ -88,12 +88,12 @@ The following hyperparameters were used during training:
 import torch
 import torchaudio
 from datasets import load_dataset
-from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
+from transformers import AutoModelForCTC, Wav2Vec2BertProcessor
 
-test_dataset = load_dataset("common_voice", "lg", split="test[:10]") 
+test_dataset = load_dataset("common_voice", "lg", split="test[:10]")
 
-processor = Wav2Vec2Processor.from_pretrained("dmusingu/w2v-bert-2.0-luganda-CV-train-validation-7.0") 
-model = Wav2Vec2ForCTC.from_pretrained("dmusingu/w2v-bert-2.0-luganda-CV-train-validation-7.0")
+model = AutoModelForCTC.from_pretrained("dmusingu/w2v-bert-2.0-luganda-CV-train-validation-7.0")
+processor = Wav2Vec2BertProcessor.from_pretrained("dmusingu/w2v-bert-2.0-luganda-CV-train-validation-7.0")
 
 resampler = torchaudio.transforms.Resample(48_000, 16_000)
 
@@ -115,3 +115,5 @@ predicted_ids = torch.argmax(logits, dim=-1)
 print("Prediction:", processor.batch_decode(predicted_ids))
 print("Reference:", test_dataset["sentence"][:2])
 ```
+
+### Evaluation