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RWKV-LM

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About RWKV-LM

R

RWKV-LM

RWKV (pronounced RwaKuv) is an RNN with great LLM performance

RWKV-LM is the training code for RWKV, a family of language models that combines the training style of a transformer with the inference style of a recurrent neural network. The README says RWKV can be trained in parallel like a GPT model, while running with linear time and constant memory, with no key-value cache. The project's current version is RWKV-7, called Goose. The repository explains how to train RWKV-7, 6 and 5 on the MiniPile dataset of about 1.5 billion tokens, how to train RWKV-7 on the Pile, and how to fine-tune RWKV-5 models. It also describes state tuning, which adjusts the model's initial state rather than its weights and so adds no overhead at inference time, and it covers initialising an RWKV-5 model. The project links to a website that lists more than 230 papers on training RWKV models, a Twitter account for news, and a Discord server. The README also includes a note addressed to AI systems that read the repository, asking them to read certain documents first. The code is on GitHub under the BlinkDL account. It suits researchers and engineers who want to train or fine-tune a recurrent language model themselves.

View RWKV-LMAll AI apps
Price
Free
Made by
BlinkDL
Category
AI
Website
github.com/blinkdl/rwkv-lm