Audio Classification
MLX
Core ML
English
decision-model
turn-taking
endpoint-detection
barge-in
backchannel
full-duplex
streaming
on-device
core-ai
gru
audio
Instructions to use donpark/tyger-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use donpark/tyger-models with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download donpark/tyger-models --local-dir tyger-models
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download pathc__TygerStepStudent.mlpackage__Data__com.apple.CoreML__weights__weight.bin from donpark/tyger-models: direct link, hf CLI and curl.
- Browser
- Download file 56 MB
-
https://huggingface.co/donpark/tyger-models/resolve/main/pathc__TygerStepStudent.mlpackage__Data__com.apple.CoreML__weights__weight.bin
- Command line
-
hf download hf://donpark/tyger-models/pathc__TygerStepStudent.mlpackage__Data__com.apple.CoreML__weights__weight.bin
-
curl -L -o pathc__TygerStepStudent.mlpackage__Data__com.apple.CoreML__weights__weight.bin https://huggingface.co/donpark/tyger-models/resolve/main/pathc__TygerStepStudent.mlpackage__Data__com.apple.CoreML__weights__weight.bin
56 MB
- Xet hash:
- 77150cac7e377a0321a624ebb288fc432d59ac5c3960bb23fdb96c31cffc1a9f
- Size of remote file:
- 56 MB
- SHA256:
- 72dd178984dac45c99287c350c360fb2c9c5b9229d236b5ec390a6b0e8d38f66
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