Any-to-Any
Transformers
Safetensors
English
dynin_omni
text-generation
diffusion
omni-modal
dllm
custom_code
Instructions to use snu-aidas/Dynin-Omni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use snu-aidas/Dynin-Omni with Transformers:
# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("snu-aidas/Dynin-Omni", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add library_name and base model metadata
#2
by nielsr HF Staff - opened
Hi, I'm Niels from the Hugging Face community team.
This PR improves the model card by:
- Adding
library_name: transformersto the metadata. Since yourconfig.jsonincludes anauto_map, this will enable the "Open in Transformers" button and help users load the model more easily. - Adding
base_model: Gen-Verse/MMaDA-8B-MixCoTas referenced in the training instructions. - Summarizing benchmark results from the paper in the Evaluation section to provide immediate context on the model's capabilities.
Hi Niels,
Thanks for the PR and for improving the model card.
I checked the changes, and everything looks good on our side.
Thanks again for the contribution.
Best regards,
Hoeun Lee
leehe228 changed pull request status to merged