Automatic Speech Recognition
NeMo
Safetensors
GGUF
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-1.1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/parakeet-ctc-1.1b with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("nvidia/parakeet-ctc-1.1b") transcriptions = asr_model.transcribe(["file.wav"]) - Transformers
How to use nvidia/parakeet-ctc-1.1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nvidia/parakeet-ctc-1.1b")# Load model directly from transformers import AutoModelForCTC model = AutoModelForCTC.from_pretrained("nvidia/parakeet-ctc-1.1b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fix the model class name EncDecCTCBPEModel -> EncDecCTCModelBPE
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by pplantinga - opened
README.md
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@@ -197,7 +197,7 @@ The model is available for use in the NeMo toolkit [3], and can be used as a pre
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```python
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import nemo.collections.asr as nemo_asr
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asr_model = nemo_asr.models.
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```
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### Transcribing using Python
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```python
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import nemo.collections.asr as nemo_asr
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asr_model = nemo_asr.models.EncDecCTCModelBPE.from_pretrained(model_name="nvidia/parakeet-ctc-1.1b")
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```
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### Transcribing using Python
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