Whisper large-v3
model·speech recognition model·active
Multilingual ASR and speech-to-English translation checkpoint.
Verified facts
| Official site | https://huggingface.co/openai/whisper-large-v3 ↗ |
|---|---|
| Geography | unknown |
| parameter count | 1.55B |
| huggingface repo | openai/whisper-large-v3 |
| api | unknown |
| inputs | audio |
| license | MIT |
| outputs | text transcription |
| weights | public |
| modalities | audio; text transcription |
| dependencies | unknown |
| model family | Whisper |
| access method | downloadable weights; openai-whisper Python package; Hugging Face Transformers |
| exact version | large-v3 |
| repository links | https://huggingface.co/openai/whisper-large-v3; https://github.com/openai/whisper |
| evaluation results | result: OpenAI reports 10% to 20% error reduction versus large-v2 for evaluated languages below 60% error. · source: https://github.com/openai/whisper/discussions/1762 · benchmark: Common Voice 15 and Fleurs |
| evidence separation | developer claims: · measured results: · independent evaluations: |
| developer maintainer | OpenAI |
| material us relevance | Publicly accessible in or materially offered to the United States market as of snapshot. |
| documented capabilities | multilingual automatic speech recognition; lyric/vocal transcription as a downstream musical workflow |
| products exposing model | unknown |
| commercial use conditions | MIT terms apply to code and weights. |
| known geographic or policy restrictions | unknown |
| safety watermarking disclosure provenance | unknown |
Sources & changes
1d ago · highhow verification works
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