Any-to-Any
Transformers
Safetensors
English
Chinese
qwen3_omni_moe
text-to-audio
multimodal
fp8
quantization
compressed-tensors
vllm
Instructions to use tturing/Qwen3-Omni-30B-A3B-Thinking-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tturing/Qwen3-Omni-30B-A3B-Thinking-FP8 with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("tturing/Qwen3-Omni-30B-A3B-Thinking-FP8") model = AutoModelForMultimodalLM.from_pretrained("tturing/Qwen3-Omni-30B-A3B-Thinking-FP8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0f1e5c29183746a6e7d0510804a0ad12c6dcf97bd859531dcfaa1ca45db4e5e
- Size of remote file:
- 5 GB
- SHA256:
- 60e5bbfb564b0afa2d6507657783ccdb69705c7cc79d93514ccc34ac837d3df1
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