Feature Extraction
Transformers
Safetensors
granite_speech_nar
speech
asr
non-autoregressive
ctc
speech_recognition
automatic_speech_recognition
custom_code
Instructions to use ibm-granite/granite-speech-4.1-2b-nar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-granite/granite-speech-4.1-2b-nar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ibm-granite/granite-speech-4.1-2b-nar", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ibm-granite/granite-speech-4.1-2b-nar", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
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