Delete inference.py

inference.py

@@ -1,31 +0,0 @@
-
-# inference.py
-from transformers import Wav2Vec2BertForCTC, Wav2Vec2BertProcessorWithLM
-import torchaudio
-import torch
-
-# Load model
-model_id = "BeitTigreAI/tigre-asr-w2v2-bert-lm"
-processor = Wav2Vec2BertProcessorWithLM.from_pretrained(model_id)
-model = Wav2Vec2BertForCTC.from_pretrained(model_id).to(
-    "cuda" if torch.cuda.is_available() else "cpu")
-
-# Load audio (16kHz mono expected)
-
-
-def load_audio(path):
-    waveform, sr = torchaudio.load(path)
-    if sr != 16000:
-        waveform = torchaudio.transforms.Resample(sr, 16000)(waveform)
-    return waveform.mean(dim=0)  # Convert to mono
-
-
-# Transcribe
-audio = load_audio("your-audio.mp3")  # Replace with your file
-inputs = processor(audio, sampling_rate=16000,
-                   return_tensors="pt").to(model.device)
-with torch.no_grad():
-    logits = model(**inputs).logits
-transcription = processor.batch_decode(logits.cpu().numpy()).text[0]
-
-print("Transcription:", transcription)