Text-to-Audio
Transformers
Safetensors
qwen3_omni_moe
rasst
infinisst
speech-translation
streaming-translation
research-artifact
Instructions to use gavinlaw/rasst-infinisst-baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gavinlaw/rasst-infinisst-baseline with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="gavinlaw/rasst-infinisst-baseline")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("gavinlaw/rasst-infinisst-baseline") model = AutoModelForMultimodalLM.from_pretrained("gavinlaw/rasst-infinisst-baseline", device_map="auto") - Notebooks
- Google Colab
- Kaggle
gavinlaw/rasst-infinisst-baseline
RASST release artifact: the InfiniSST no-RAG baseline Speech-LLM (Qwen3-Omni-30B-A3B-Instruct, LoRA r16,
sampling variant, merged to a Hugging Face model directory). It is the model_infinisst_baseline asset of the
RASST main_result_baseline_no_rag manifest and receives no retrieved terms; args.json holds the training
arguments.
Training speech comes from GigaSpeech, which may be used only for non-commercial research and education, so these weights are released under CC BY-NC 4.0.
See the RASST repository for manifests and launch wrappers: https://github.com/luojiaxuan/RASST
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Model tree for gavinlaw/rasst-infinisst-baseline
Base model
Qwen/Qwen3-Omni-30B-A3B-Instruct