Automatic Speech Recognition
Transformers
Safetensors
English
whisper
FP8
vllm
audio
compressed-tensors
Instructions to use RedHatAI/whisper-small-FP8-Dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RedHatAI/whisper-small-FP8-Dynamic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="RedHatAI/whisper-small-FP8-Dynamic")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("RedHatAI/whisper-small-FP8-Dynamic") model = AutoModelForSpeechSeq2Seq.from_pretrained("RedHatAI/whisper-small-FP8-Dynamic") - Notebooks
- Google Colab
- Kaggle
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<td rowspan="3"><b>Fleurs (X→en, BLEU)</b></td>
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<td>cmn_hans_cn</td>
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<td rowspan="3"><b>Fleurs (X→en, BLEU)</b></td>
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<td>cmn_hans_cn</td>
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<td>23.0642</td>
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<td>24.6761</td>
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<td>93.50%</td>
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<td>en</td>
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<td>6.2002</td>
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<td>6.1110</td>
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<td>101.46%</td>
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<td>yue_hant_hk</td>
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<td>16.2557</td>
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<td>18.1627</td>
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<td>89.50%</td>
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