This is the Linux app named rwkv.cpp whose latest release can be downloaded as rwkv-master-d6c691e-bin-win-avx512-x64.zip. It can be run online in the free hosting provider OnWorks for workstations.
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rwkv.cpp
DESCRIPTION
Besides the usual FP32, it supports FP16, quantized INT4, INT5 and INT8 inference. This project is focused on CPU, but cuBLAS is also supported. RWKV is a novel large language model architecture, with the largest model in the family having 14B parameters. In contrast to Transformer with O(n^2) attention, RWKV requires only state from the previous step to calculate logits. This makes RWKV very CPU-friendly on large context lengths.
Features
- Windows / Linux / MacOS
- Build the library yourself
- Get an RWKV model
- Requirements: Python 3.x with PyTorch and tokenizers
- ggml moves fast, and can occasionally break compatibility with older file formats
- Requirements: Python 3.x with PyTorch
Programming Language
C++
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/rwkv-cpp.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
