🎙️ Speech Recognition

whisperkit-coreml

argmaxinc/whisperkit-coreml

Get AI Model →
7.0M
Downloads
❤️
169
Likes
🏷️
7
Tags
📦
whisperkit
Library
Model Details
Full Model IDargmaxinc/whisperkit-coreml
Pipeline / Taskautomatic-speech-recognition
Librarywhisperkit
Downloads (all-time)7.0M
Likes169
Last Modified1/27/2026
Author / Orgargmaxinc
PrivateNo — public
⚡ Quick Usage (Python)

Using the 🤗 Transformers library. Install with pip install transformers

from transformers import pipeline

# Load the model
pipe = pipeline("automatic-speech-recognition", model="argmaxinc/whisperkit-coreml")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
whisperkitcoremlwhisperasrquantizedautomatic-speech-recognitionregion:us
More Speech Recognition Models
See all →
speaker-diarization-3.1

pyannote/speaker-diarization-3.1

10.2M❤️ 1.8K
Get AI Model →
whisper-large-v3-turbo

openai/whisper-large-v3-turbo

6.7M❤️ 3.0K
Get AI Model →
wav2vec2-large-xlsr-53-russian

jonatasgrosman/wav2vec2-large-xlsr-53-russian

5.2M❤️ 67
Get AI Model →
🚀 Use This Model

Access model files, inference API, and full documentation on Hugging Face.

Open on Hugging Face →Browse Model Files ↗← Browse All Models
🎙️ Task: Speech Recognition

This model is designed for the Speech Recognition task. Explore more models for this use case.

All Speech Recognition Models →
📊 Popularity
Downloads7.0M
❤️ Community Likes169
🛠️ Requirements
  • Install: pip install whisperkit
  • Python 3.8+ recommended for Transformers.
  • GPU (CUDA) speeds up inference significantly.
  • Use model.half() for fp16 on limited VRAM.
👋 Need help with code?