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:
- 7e93d54c3c481d4b337d1f8d6185fe40d997b367fe550a814ef23dc5f335c443
- Size of remote file:
- 2.55 GB
- SHA256:
- 9eebdd6590289cb3030f310858f3df93256600a800a3e8200c5993d5f967e174
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