Instructions to use slprl/SIMS-Llama3.2-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slprl/SIMS-Llama3.2-3B with Transformers:
# Load model directly from transformers import UnitLM model = UnitLM.from_pretrained("slprl/SIMS-Llama3.2-3B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update pipeline tag to audio-text-to-text
This PR updates the pipeline_tag for the model card from audio-to-audio to audio-text-to-text.
The model is described as an "Interleaved Speech-Text Language Model" that can generate "speech or text continuations over discrete Hubert tokens given speech-text prompts." This indicates that it processes both speech and text as input and can generate both speech (via vocoding Hubert tokens) and text as output. The audio-text-to-text pipeline tag accurately reflects this multi-modal input and output capability, improving the model's discoverability and categorization on the Hugging Face Hub.
Hey, perhaps I am mis-understanding but audio-text-to-text indicates that the model only outputs text while in reality in can output speech as well. It would be nice to indicate that it also handles text but I could not find a suitable tag.