Update README.md

README.md

@@ -69,38 +69,6 @@ Users (both direct and downstream) should be made aware of the risks, biases and
 
 Use the code below to get started with the model.
 
-### Running the model 
-
-<details>
-<summary> Click to expand </summary>
-```python
-
-!pip install transformers datasets torchaudio
-
-from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
-import torch
-import torchaudio
-
-model_id = "fastinom/ASR_fassy"
-model = Wav2Vec2ForCTC.from_pretrained(model_id)
-processor = Wav2Vec2Processor.from_pretrained(model_id)
-
-def load_audio(file_path):
-    speech_array, sampling_rate = torchaudio.load(file_path)
-    resampler = torchaudio.transforms.Resample(sampling_rate, 16000)
-    speech = resampler(speech_array).squeeze().numpy()
-    return speech
-audio_file = "/content/drive/MyDrive/recordings/wavefiles/1.wa"#YOUR AUDIO PATH
-speech = load_audio(audio_file)
-
-inputs = processor(speech, sampling_rate=16000, return_tensors="pt", padding=True)
-with torch.no_grad():
-    logits = model(inputs.input_values).logits
-predicted_ids = torch.argmax(logits, dim=-1)
-transcription = processor.batch_decode(predicted_ids)
-print(transcription[0])
-```
-</details>]
 
 ## Training Details