torchscale VS RetNet

Compare torchscale vs RetNet and see what are their differences.

RetNet

An implementation of "Retentive Network: A Successor to Transformer for Large Language Models" (by Jamie-Stirling)
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torchscale RetNet
2 2
2,927 1,125
1.6% -
7.2 7.2
25 days ago 7 months ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

torchscale

Posts with mentions or reviews of torchscale. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-07-24.

RetNet

Posts with mentions or reviews of RetNet. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-07-24.

What are some alternatives?

When comparing torchscale and RetNet you can also consider the following projects:

towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

fairscale - PyTorch extensions for high performance and large scale training.

bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

extreme-bert - ExtremeBERT is a toolkit that accelerates the pretraining of customized language models on customized datasets, described in the paper “ExtremeBERT: A Toolkit for Accelerating Pretraining of Customized BERT”.

xformers - Hackable and optimized Transformers building blocks, supporting a composable construction.

glami-1m - The largest multilingual image-text classification dataset. It contains fashion products.

transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Multimodal-GPT - Multimodal-GPT