Automatic Speech Recognition
Transformers
Safetensors
English
whisper
w8a8
INT8
vllm
audio
8-bit precision
compressed-tensors
Instructions to use RedHatAI/whisper-medium-quantized.w8a8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RedHatAI/whisper-medium-quantized.w8a8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="RedHatAI/whisper-medium-quantized.w8a8")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("RedHatAI/whisper-medium-quantized.w8a8") model = AutoModelForSpeechSeq2Seq.from_pretrained("RedHatAI/whisper-medium-quantized.w8a8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 215 Bytes
f069f66 | 1 2 3 4 5 6 7 8 9 | DEFAULT_stage:
DEFAULT_modifiers:
GPTQModifier:
sequential_targets: [WhisperEncoderLayer, WhisperDecoderLayer]
dampening_frac: 0.03
scheme: W8A8
targets: Linear
ignore: [lm_head]
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