Can Distilled Whisper Models be used as a Drop-In Replacement for OpenAI Whisper?

I have a working video transcription pipeline working using a local OpenAI Whisper model. I would like to use the equivalent distilled model ("distil-small.en"), which is smaller and faster.

transcribe(self):    file = "/path/to/video"    model = whisper.load_model("small.en")          # WORKS    model = whisper.load_model("distil-small.en")   # DOES NOT WORK     transcript = model.transcribe(word_timestamps=True, audio=file)    print(transcript["text"])

However, I get an error that the model was not found:

RuntimeError: Model distil-small.en not found; available models = ['tiny.en', 'tiny', 'base.en', 'base', 'small.en', 'small', 'medium.en', 'medium', 'large-v1', 'large-v2', 'large-v3', 'large']

I installed my dependencies in Poetry (which used pip under the hood) as follows:

[tool.poetry.dependencies]python = "^3.11"openai-whisper = "*"transformers  = "*" # distilled whisper modelsaccelerate  = "*" # distilled whisper modelsdatasets = { version = "*", extras = ["audio"] } # distilled whisper models

The GitHub Distilled Whisper documentation appears to use a different approach to installing and using these models.

Is it possible to use a Distilled model as a drop-in replacement for a regular Whisper model?