Instructions to use ibm-granite/granite-4.0-1b-speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-granite/granite-4.0-1b-speech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ibm-granite/granite-4.0-1b-speech")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ibm-granite/granite-4.0-1b-speech") model = AutoModelForMultimodalLM.from_pretrained("ibm-granite/granite-4.0-1b-speech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Updated English WER chart
Browse files
README.md
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We evaluated granite-4.0-1b-speech alongside other speech-language models in the less than 8b parameter range as well as dedicated ASR and AST systems on standard benchmarks. The evaluation spanned multiple public benchmarks, with particular emphasis on English ASR tasks while also including multilingual ASR and AST for X-En and En-X translations.
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We evaluated granite-4.0-1b-speech alongside other speech-language models in the less than 8b parameter range as well as dedicated ASR and AST systems on standard benchmarks. The evaluation spanned multiple public benchmarks, with particular emphasis on English ASR tasks while also including multilingual ASR and AST for X-En and En-X translations.
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