Automatic Speech Recognition
MLX
Safetensors
Japanese
apple-silicon
japanese
speech-recognition
asr
parakeet
tdt
fastconformer
Instructions to use basyauma-tech/Haas-ja-v1.0-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use basyauma-tech/Haas-ja-v1.0-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download basyauma-tech/Haas-ja-v1.0-mlx --local-dir Haas-ja-v1.0-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer.model from basyauma-tech/Haas-ja-v1.0-mlx: direct link, hf CLI and curl.
- Browser
- Download file 280 kB
-
https://huggingface.co/basyauma-tech/Haas-ja-v1.0-mlx/resolve/main/tokenizer.model
- Command line
-
hf download hf://basyauma-tech/Haas-ja-v1.0-mlx/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/basyauma-tech/Haas-ja-v1.0-mlx/resolve/main/tokenizer.model
280 kB
- Xet hash:
- 508d41823d4de57d152f5219429f75ce4ec013efddb1db55d8f0a7767228e8f5
- Size of remote file:
- 280 kB
- SHA256:
- 9bd7bcdff62e43200001cd4c258d22e475b7b3b1e0f64f8be8e6e046f402f38c
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