| --- |
| license: other |
| track_downloads: true |
| language: |
| - en |
| pipeline_tag: automatic-speech-recognition |
| library_name: mlx |
| datasets: |
| - nvidia/Granary |
| - YTC |
| - Yodas2 |
| - LibriLight |
| - librispeech_asr |
| - fisher_corpus |
| - Switchboard-1 |
| - WSJ-0 |
| - WSJ-1 |
| - National-Singapore-Corpus-Part-1 |
| - National-Singapore-Corpus-Part-6 |
| - vctk |
| - voxpopuli |
| - europarl |
| - multilingual_librispeech |
| - fleurs |
| - mozilla-foundation/common_voice_8_0 |
| - MLCommons/peoples_speech |
| - google/speech_commands |
| tags: |
| - quantized |
| - speech-recognition |
| - cache-aware ASR |
| - automatic-speech-recognition |
| - streaming-asr |
| - speech |
| - audio |
| - FastConformer |
| - RNNT |
| - Parakeet |
| - ASR |
| - pytorch |
| - NeMo |
| - mlx |
| base_model: nvidia/nemotron-speech-streaming-en-0.6b |
| base_model_relation: quantized |
| --- |
| |
| # **animaslabs/nemotron-speech-streaming-en-0.6b-mlx-8bit** |
|
|
| This model was converted to MLX format, 8-bit quantized from [nvidia/nemotron-speech-streaming-en-0.6b](https://huggingface.co/nvidia/nemotron-speech-streaming-en-0.6b) using the scripts in this [github repo](https://github.com/animaslabs/mlx-models). Please refer to [original model card](https://huggingface.co/nvidia/nemotron-speech-streaming-en-0.6b) for more details on the model. |
|
|
| ## Usage |
|
|
| Quantized models require calling `mlx.nn.quantize()` before loading weights. |
|
|
| ```python |
| import json |
| import mlx.nn as nn |
| from huggingface_hub import hf_hub_download |
| from parakeet_mlx.utils import from_config |
| |
| # Download and load config |
| config_path = hf_hub_download("animaslabs/nemotron-speech-streaming-en-0.6b-mlx-8bit", "config.json") |
| with open(config_path) as f: |
| config = json.load(f) |
| |
| # Build model and apply quantization structure |
| model = from_config(config) |
| nn.quantize( |
| model, |
| bits=config["quantization"]["bits"], |
| group_size=config["quantization"]["group_size"], |
| ) |
| |
| # Load quantized weights |
| weights_path = hf_hub_download("animaslabs/nemotron-speech-streaming-en-0.6b-mlx-8bit", "model.safetensors") |
| model.load_weights(weights_path) |
| |
| # Transcribe |
| result = model.transcribe("audio.wav") |
| print(result.text) |
| ``` |
|
|
|
|
