I did some testing on the scalability of FWKV. It hits a speed bottleneck at 1B due to the T4’s bandwidth limitations. Theoretically, it should match RWKV’s inference speed if the GPU had more bandwidth. So the 1B size is not accurate.
I started a new project called **FWKV** (Feed-forward Weighted Key Value, or Floored Weighted Key Value), a RWKV-style LM that uses FFNNs (Feed-Forward Neural Networks) instead of RNN and floor(W·K·V). I'm hoping to make it much more efficient and scalable than RWKV.
So far I have:
- FlameF0X/FWKV-29M — this one is undertrained and doesn't have a Space yet. In the attached image you can see its speed on a T4 compared to models with the same configuration.