Automatic Speech Recognition
NeMo
Safetensors
Transformers
PyTorch
nemotron3_5_asr
feature-extraction
speech-recognition
cache-aware ASR
streaming-asr
multilingual
speech
audio
FastConformer
RNNT
Parakeet
ASR
NeMo
Eval Results (legacy)
Instructions to use 0x3/nemotron-3.5-asr-streaming-0.6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use 0x3/nemotron-3.5-asr-streaming-0.6b with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("0x3/nemotron-3.5-asr-streaming-0.6b") transcriptions = asr_model.transcribe(["file.wav"]) - Transformers
How to use 0x3/nemotron-3.5-asr-streaming-0.6b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="0x3/nemotron-3.5-asr-streaming-0.6b")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("0x3/nemotron-3.5-asr-streaming-0.6b") model = AutoModel.from_pretrained("0x3/nemotron-3.5-asr-streaming-0.6b") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 0375b807e49bbe1998b07f4330bc1572e4511ae3251c9d0923aceff11a7c2212
- Size of remote file:
- 83.8 kB
- SHA256:
- 56c360a710c99cbf70c04006ec1f842b3796b72f5093178d438b2140049b3626
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