RWKV-CUDA
RWKV-infctx-trainer
| RWKV-CUDA | RWKV-infctx-trainer | |
|---|---|---|
| 3 | 1 | |
| 220 | 148 | |
| 1.4% | 4.7% | |
| 2.9 | 9.3 | |
| 3 months ago | 8 months ago | |
| Cuda | Jupyter Notebook | |
| - | Apache License 2.0 |
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RWKV-CUDA
- People who've used RWKV, whats your wishlist for it?
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Accelerate PyTorch with Taichi: Data Preprocessing & High-performance ML Operator Customization
This repo introduces an interesting example of customizing an ML operator in CUDA. The author developed an RWKV language model using sort of a one-dimensional depthwise convolution custom operator. The model in itself does not involve large amounts of computation, but still runs slow because PyTorch does not have native support for it. So, the author customized the operator in CUDA and used a set of optimization techniques, such as loop fusion and Shared Memory, achieving a performance 20x better than he did with PyTorch.
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[R] RWKV-v2-RNN : A parallelizable RNN with transformer-level LM performance, and without using attention
It's using my custom CUDA kernel ( https://github.com/BlinkDL/RWKV-CUDA ) to speedup training, so only GPU for now. On the other hand, you don't need CUDA for inference, and it is very fast even on CPUs.
RWKV-infctx-trainer
What are some alternatives?
RWKV-LM - RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
faster-rwkv
RWKV-v2-RNN-Pile - RWKV-v2-RNN trained on the Pile. See https://github.com/BlinkDL/RWKV-LM for details.
RWKV-LM-LoRA - RWKV is a RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
web-rwkv - Implementation of the RWKV language model in pure WebGPU/Rust.