Automatic Speech Recognition
NeMo
Safetensors
Transformers
PyTorch
English
parakeet_ctc
speech
audio
FastConformer
Conformer
NeMo
hf-asr-leaderboard
ctc
Eval Results (legacy)
Eval Results
Instructions to use nvidia/parakeet-ctc-0.6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/parakeet-ctc-0.6b with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("nvidia/parakeet-ctc-0.6b") transcriptions = asr_model.transcribe(["file.wav"]) - Transformers
How to use nvidia/parakeet-ctc-0.6b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nvidia/parakeet-ctc-0.6b")# Load model directly from transformers import AutoModelForCTC model = AutoModelForCTC.from_pretrained("nvidia/parakeet-ctc-0.6b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 962 Bytes
ad09ba1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | {
"architectures": [
"ParakeetForCTC"
],
"ctc_loss_reduction": "mean",
"ctc_zero_infinity": true,
"dtype": "bfloat16",
"encoder_config": {
"activation_dropout": 0.1,
"attention_bias": true,
"attention_dropout": 0.1,
"conv_kernel_size": 9,
"dropout": 0.1,
"dropout_positions": 0.0,
"hidden_act": "silu",
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 4096,
"layerdrop": 0.1,
"max_position_embeddings": 5000,
"model_type": "parakeet_encoder",
"num_attention_heads": 8,
"num_hidden_layers": 24,
"num_key_value_heads": 8,
"num_mel_bins": 80,
"scale_input": true,
"subsampling_conv_channels": 256,
"subsampling_conv_kernel_size": 3,
"subsampling_conv_stride": 2,
"subsampling_factor": 8
},
"initializer_range": 0.02,
"model_type": "parakeet_ctc",
"pad_token_id": 1024,
"transformers_version": "4.57.0.dev0",
"vocab_size": 1025
}
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