Automatic Speech Recognition
Transformers
Safetensors
English
whisper
FP8
vllm
audio
compressed-tensors
Instructions to use RedHatAI/whisper-tiny-FP8-Dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RedHatAI/whisper-tiny-FP8-Dynamic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="RedHatAI/whisper-tiny-FP8-Dynamic")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("RedHatAI/whisper-tiny-FP8-Dynamic") model = AutoModelForSpeechSeq2Seq.from_pretrained("RedHatAI/whisper-tiny-FP8-Dynamic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 892978621ed0b35d11a5d675af18ebc84171ee8562b2e971e51fd2fc31d60dea
- Size of remote file:
- 122 MB
- SHA256:
- f0d38f0a7222c8e0b692f7c773e76b64b9f6494f032e07d05bd9f6edbc1201b8
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