Automatic Speech Recognition
MLX
Russian
speech-recognition
russian
offline
apple
apple-silicon
ios
ipados
macos
rnnt
conformer
sentencepiece
native-apple
Instructions to use kruatech/gigaam-v3-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use kruatech/gigaam-v3-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download kruatech/gigaam-v3-mlx --local-dir gigaam-v3-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download tokenizer.model from kruatech/gigaam-v3-mlx: direct link, hf CLI and curl.
- Browser
- Download file 255 kB
-
https://huggingface.co/kruatech/gigaam-v3-mlx/resolve/main/tokenizer.model
- Command line
-
hf download hf://kruatech/gigaam-v3-mlx/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/kruatech/gigaam-v3-mlx/resolve/main/tokenizer.model
255 kB
- Xet hash:
- 988ec114e7c6625b5f18e331361fab1f1bde6ced0fe305c6ab55dbccd39c9119
- Size of remote file:
- 255 kB
- SHA256:
- 828c12c991019eef952a960661f25a92d6ad279591e2ea466b4aeddf1d20a18a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.