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:
- b11e03b2bac3c3856c99b9843db2fc75f4f96f4b7a51dfc45ac7a5d4b494d723
- Size of remote file:
- 5 GB
- SHA256:
- d1be12d5e2e586561b844f5e9a2c9bfb2604f2e243e0cf4fe28cb32217771163
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