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
| Field | Response |
|---|---|
| Generatable or reverse engineerable personal data? | No |
| Personal data used to create this model? | Yes - Voice |
| Was consent obtained for any personal data used? | Yes |
| Is a mechanism in place to honor data subject right of access or deletion of personal data? | Yes |
| If personal data was collected for the development of the model, was it collected directly by NVIDIA? | Yes |
| If personal data was collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Yes |
| If personal data was collected for the development of this AI model, was it minimized to only what was required? | Yes |
| Is there provenance for all datasets used in training? | Yes |
| Does data labeling (annotation, metadata) comply with privacy laws? | Yes |
| Is data compliant with data subject requests for data correction or removal, if such a request was made? | No, not possible with externally-sourced data. |
| Applicable Privacy Policy | https://www.nvidia.com/en-us/about-nvidia/privacy-policy/ |
| How often is dataset reviewed? | Dataset is initially reviewed upon addition, and subsequent reviews are conducted as needed or upon request for changes. |
| Was data from user interactions with the AI model (e.g. user input and prompts) used to train the model? | No |