Delete benchmark_hf_pipeline.py

benchmark_hf_pipeline.py

@@ -1,27 +0,0 @@
-from pprint import pprint
-from transformers import pipeline
-from datasets import load_dataset
-
-# config
-model_id = "kotoba-tech/kotoba-whisper-v1.0"
-generate_kwargs = {"language": "japanese", "task": "transcribe"}
-
-# load model
-pipe = pipeline(
-    "automatic-speech-recognition",
-    model=model_id,
-    chunk_length_s=15,
-    batch_size=64
-)
-test_audio = [
-    "kotoba-whisper-eval/audio/long_interview_1.wav",
-    "kotoba-whisper-eval/audio/manzai1.wav",
-    "kotoba-whisper-eval/audio/manzai2.wav",
-    "kotoba-whisper-eval/audio/manzai3.wav"
-]
-elapsed = {}
-for x in test_audio:
-    start = time()
-    transcription = pipe(x, generate_kwargs=generate_kwargs)
-    elapsed[x] = time() - start
-pprint(elapsed)