Instructions to use ModalityDance/MRM-PRISM-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModalityDance/MRM-PRISM-V1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModalityDance/MRM-PRISM-V1")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ModalityDance/MRM-PRISM-V1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add transformers library tag and improve model card
Verified signatureHi! I'm Niels from the Hugging Face community science team. This PR adds the `library_name: transformers` and `pipeline_tag: text-classification` tags to the model metadata. This will help improve the model's discoverability and enable the "Use in Transformers" button on the repository. I have also linked the model card to the accompanying paper: [One Adapts to Any: Meta Reward Modeling for Personalized LLM Alignment](https://huggingface.co/papers/2601.18731).60fee0f
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Upload folder using huggingface_hub
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