A New Time Series Similarity Measure and Its Smart Grid Applications
Paper • 2310.12399 • Published
How to use aitytech/Parakeet-TDT-0.6B-v3-MLX-FP16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Parakeet-TDT-0.6B-v3-MLX-FP16 aitytech/Parakeet-TDT-0.6B-v3-MLX-FP16
How to use aitytech/Parakeet-TDT-0.6B-v3-MLX-FP16 with NeMo:
import nemo.collections.asr as nemo_asr
asr_model = nemo_asr.models.ASRModel.from_pretrained("aitytech/Parakeet-TDT-0.6B-v3-MLX-FP16")
transcriptions = asr_model.transcribe(["file.wav"])This is the NVIDIA Parakeet TDT 0.6B model converted to MLX format with FP16 precision, optimized for Apple Silicon inference.
Parakeet TDT is an ASR model based on the Token-and-Duration Transducer (TDT) architecture, trained on large-scale speech data. The v3 variant adds support for 25 European languages beyond the original English-only v2.
| Property | Value |
|---|---|
| Base Model | nvidia/parakeet-tdt-0.6b-v2 |
| Parameters | ~600M |
| Format | MLX SafeTensors (FP16) |
| Model Size | 1,196.08 MB |
| Sample Rate | 16,000 Hz |
| Architecture | FastConformer + TDT |
| Encoder Hidden | 1024 |
| Predictor Hidden | 640 |
| Joint Hidden | 640 |
| TDT Durations | [0, 1, 2, 3, 4] |
| Tokenizer | BPE |
| Language | 25 European languages (BG, CS, DA, DE, EL, EN, ES, ET, FI, FR, HR, HU, IT, LT, LV, MT, NL, PL, PT, RO, RU, SK, SL, SV, UK) |
This model is optimized for on-device automatic speech recognition (ASR) on Apple Silicon devices (Mac, iPhone, iPad). It supports 25 European languages: BG, CS, DA, DE, EL, EN, ES, ET, FI, FR, HR, HU, IT, LT, LV, MT, NL, PL, PT, RO, RU, SK, SL, SV, UK.
config.json - Model configurationmodel.safetensors - Model weights in SafeTensors format (FP16)tokenizer.model - SentencePiece tokenizer modeltokenizer.vocab - Tokenizer vocabularyvocab.txt - Vocabulary text fileQuantized
Base model
nvidia/parakeet-tdt-0.6b-v2