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
| { | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "1024": { | |
| "content": "<pad>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "clean_up_tokenization_spaces": false, | |
| "extra_special_tokens": {}, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "processor_class": "ParakeetProcessor", | |
| "tokenizer_class": "ParakeetTokenizerFast", | |
| "unk_token": "<unk>" | |
| } | |