Implementation of Griffin from the paper: "Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models". PAPER LINK
$ pip install griffin-torch
import torch from griffin_torch.main import Griffin # Forward pass x = torch.randint(0, 100, (1, 10)) # Model model = Griffin( dim=512, # Dimension of the model num_tokens=100, # Number of tokens in the input seq_len=10, # Length of the input sequence depth=8, # Number of transformer blocks mlp_mult=4, # Multiplier for the hidden dimension in the MLPs dropout=0.1, # Dropout rate ) # Forward pass y = model(x) print(y)MIT
@misc{de2024griffin, title={Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models}, author={Soham De and Samuel L. Smith and Anushan Fernando and Aleksandar Botev and George Cristian-Muraru and Albert Gu and Ruba Haroun and Leonard Berrada and Yutian Chen and Srivatsan Srinivasan and Guillaume Desjardins and Arnaud Doucet and David Budden and Yee Whye Teh and Razvan Pascanu and Nando De Freitas and Caglar Gulcehre}, year={2024}, eprint={2402.19427}, archivePrefix={arXiv}, primaryClass={cs.LG} }