File size: 1,766 Bytes
ddd4f45 93529c3 ddd4f45 c980508 ddd4f45 c980508 ddd4f45 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | ---
license: apache-2.0
base_model: openai/whisper-tiny.en
library_name: basert
pipeline_tag: automatic-speech-recognition
tags:
- basert
- apple-silicon
- whisper
- speech-recognition
---
# whisper-tiny.en
[BaseRT](https://github.com/basecompute/baseRT) `.base` build of
[`openai/whisper-tiny.en`](https://huggingface.co/openai/whisper-tiny.en),
OpenAI's 39M-parameter Whisper speech-recognition model (English-only),
for fast local transcription on Apple Silicon.
## Files
| File | Precision | Size |
|------|-----------|------|
| `whisper-tiny.en-F16.base` | float16 | 79 MB |
| `whisper-tiny.en-Q8.base` | 8-bit linears, f16 embeddings/conv/norms | 62 MB |
| `whisper-tiny.en-Q4.base` | 4-bit linears, f16 embeddings/conv/norms | 55 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-tiny.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-tiny.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.
|