| --- |
| license: apache-2.0 |
| base_model: openai/whisper-base.en |
| library_name: basert |
| pipeline_tag: automatic-speech-recognition |
| tags: |
| - basert |
| - apple-silicon |
| - whisper |
| - speech-recognition |
| --- |
| |
| # whisper-base.en |
|
|
| [BaseRT](https://github.com/basecompute/baseRT) `.base` build of |
| [`openai/whisper-base.en`](https://huggingface.co/openai/whisper-base.en), |
| OpenAI's 74M-parameter Whisper speech-recognition model (English-only), |
| for fast local transcription on Apple Silicon. |
|
|
| ## Files |
|
|
| | File | Precision | Size | |
| |------|-----------|------| |
| | `whisper-base.en-F16.base` | float16 | 149 MB | |
| | `whisper-base.en-Q8.base` | 8-bit linears, f16 embeddings/conv/norms | 106 MB | |
| | `whisper-base.en-Q4.base` | 4-bit linears, f16 embeddings/conv/norms | 86 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-base.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: |
|
|
| ```bash |
| basert-transcribe whisper-base.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. |
|
|
