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basecompute/
whisper-medium.en

Name: whisper-medium.en
Availability: InStock

automatic-speech-recognition

openai/whisper-medium.en

finetune

apache-2.0

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whisper-medium.en

BaseRT .base build of openai/whisper-medium.en, OpenAI's 769M-parameter Whisper speech-recognition model (English-only), for fast local transcription on Apple Silicon.

Files

File	Precision	Size
`whisper-medium.en-F16.base`	float16	1.54 GB
`whisper-medium.en-Q8.base`	8-bit linears, f16 embeddings/conv/norms	855 MB
`whisper-medium.en-Q4.base`	4-bit linears, f16 embeddings/conv/norms	524 MB

F16 and Q8 are transcription-quality equivalent (Q8 passes the same word-error parity gates against reference openai-whisper). Q4 is the smallest and remains accurate; on some smaller variants it can occasionally repeat a word in timestamped beam decoding.

Usage

bash

curl -LsSf https://basecompute.co/install.sh | sh
basert serve --model whisper-medium.en-F16.base

POST /v1/audio/transcriptions (multipart or JSON) returns json, text, srt, vtt, or verbose_json (with per-segment avg_logprob / no_speech_prob / compression_ratio / temperature and the detected language), with optional SSE streaming. Supported request fields: language (or "auto" to detect), prompt (initial prompt / vocabulary bias). Or transcribe directly from the CLI:

basert-transcribe whisper-medium.en-F16.base audio.wav

This is the English-only variant; language is fixed to en and task=translate is rejected.

Released under the apache-2.0 license, inherited from the base model.

basecompute/whisper-medium.en

whisper-medium.en

Files

Usage

basecompute/
whisper-medium.en