Any-to-Any
Transformers
Diffusers
Safetensors
English
Chinese
grin_qwen2_vl
text-generation
MoE
Omnimodal Large Model
Speech-Driven Multimodal Interaction
Image Generating and Editing
Instructions to use HIT-TMG/Uni-MoE-2.0-Omni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HIT-TMG/Uni-MoE-2.0-Omni with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("HIT-TMG/Uni-MoE-2.0-Omni", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download imgs/results.png from HIT-TMG/Uni-MoE-2.0-Omni: direct link, hf CLI and curl.
- Browser
- Download file 309 kB
-
https://huggingface.co/HIT-TMG/Uni-MoE-2.0-Omni/resolve/main/imgs/results.png
- Command line
-
hf download hf://HIT-TMG/Uni-MoE-2.0-Omni/imgs/results.png
-
curl -L -o results.png https://huggingface.co/HIT-TMG/Uni-MoE-2.0-Omni/resolve/main/imgs/results.png
309 kB

- Xet hash:
- 2edc8a880cddbd2f872ff75fe7e2ea4d1b058b0acf7d2f40f7e3d75d3fe84706
- Size of remote file:
- 309 kB
- SHA256:
- 1ef35b428fe4b0b20bd25ba62fe6f74e30ef350d4dffd22299b621e0596ec72a
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