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

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License

MIT License

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Additional Project Details

Programming Language

C++

Related Categories

C++ Large Language Models (LLM), C++ AI Models, C++ LLM Inference Tool

Registered

2023-08-25