Instructions to use Matir/granite-speech-4.1-2b-plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matir/granite-speech-4.1-2b-plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Matir/granite-speech-4.1-2b-plus")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Matir/granite-speech-4.1-2b-plus") model = AutoModelForMultimodalLM.from_pretrained("Matir/granite-speech-4.1-2b-plus", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77d187e17553e2449dd64c653ebde0a6330052bd9153256987e277d1a1b90e8b
- Size of remote file:
- 1.99 GB
- SHA256:
- 172bddcb0b9fe4e59b4302eecc478bbe5fb477759b80a52e476b43b55c9493a7
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