Instructions to use leonardklin/B3D-RWKV with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- RWKV
How to use leonardklin/B3D-RWKV with RWKV:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Triplet-Block Diffusion RWKV
This repository contains the checkpoint of B3D-RWKV, a 7.2B-parameter RWKV language model presented in the paper Triplet-Block Diffusion RWKV.
B3D-RWKV is a diffusion RWKV variant that integrates the model's $O(L)$ inference efficiency with parallel, bidirectional discrete-diffusion through a triplet-block layout method. It reaches comparable accuracy on an 8-task suite versus existing models while significantly outperforming baselines in decoding throughput with an average of 1.6× speedup.
- Paper: Triplet-Block Diffusion RWKV
- Code: GitHub Repository
Usage
For usage, please see the B3D-RWKV infer and serve directories in the official repository for instructions on how to run inference and serve the model.
Note: This checkpoint is a supervised fine-tuned (SFT) version of rwkv7-g1f-7.2B.
Citation
@misc{lin2026tripletblockdiffusionrwkv,
title={Triplet-Block Diffusion RWKV},
author={Ke Lin and Yiyang Luo and Zhaolong Su and Yunya Song and Anyi Rao},
year={2026},
eprint={2605.25969},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2605.25969},
}
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