Downloads · 30 days
50
15% of all-time downloads
MahmoudAshraf/acft-whisper-large-v3-turbo
acft-whisper-large-v3-turbo is a automatic speech recognition model from MahmoudAshraf. Use it when you need speech turned into text. The card lists the license as apache-2.0.
This is in a fine-tuned series of OpenAI's Whisper models.
Downloads · 30 days
50
15% of all-time downloads
All-time downloads
342
Public
Parameters
809M
1.6 GB on disk
Likes
3
Public
Click a slice to open those files.
.safetensors1.6 GB · 100%
From the Hugging Face model README
This is in a fine-tuned series of OpenAI's Whisper models.
The models have been finetuned for dynamic audio context robustness, allowing shorter audio contexts for better performance with short audio inputs. The method is detailed in our GitHub repo.
These models are not useful by themselves under default Whisper runtime configurations.
The easiest way to test differing audio context is to use whisper.cpp with the --audio-context parameter. We provide converted whisper.cpp models in our GitHub README.
Speed was evaluated using TensorRT-LLM using In-flight Batching Dynamic context was padded with additional 128 context for stability
| Model Name | WER on Earnings22 | Relative Speed |
|---|---|---|
| Large-V3 Full Context | 15.283 | 1.0x |
| Large-V3 Dynamic Context | 17.515 | 2.1x |
| MahmoudAshraf/acft-whisper-large-v3 | 15.381 | 2.1x |
| Large-V3 Turbo Full Context | 15.373 | 1.9x |
| Large-V3 Turbo Dynamic Context | 62.921 | 6.4x |
| This Model | 15.605 | 5.1x |
More information can be found in this GitHub README.