BERT-pytorch
transformer-pytorch
Our great sponsors
| BERT-pytorch | transformer-pytorch | |
|---|---|---|
| 1 | 2 | |
| 5,995 | 2,152 | |
| - | - | |
| 0.0 | 2.1 | |
| 8 months ago | 12 days ago | |
| Python | Python | |
| Apache License 2.0 | - |
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.
BERT-pytorch
-
Lack of activation in transformer feedforward layer?
I'm curious as to why the second matrix multiplication is not followed by an activation unlike the first one. Is there any particular reason why a non-linearity would be trivial or even avoided in the second operation? For reference, variations of this can be witnessed in a number of different implementations, including BERT-pytorch and attention-is-all-you-need-pytorch.
transformer-pytorch
-
Is GPT actually using the encoder NOT the decoder part of the transformer?
In the original paper they mention they are only using the decoder part of the model. However, their description and implementations seem to be using the encoder part of the transformer not the encoder. For example, this implementation of the original transformer encoder layer matches what the one in the GPT implementation.
-
[P] Implementation of Transformer with detailed and easy description comments
I implemented the Transformer model of Google Brain using Pytorch. It was specially written together in very detailed and easy explanatory comments. If you're a beginner who wants to implement Transformer, look at my code and try it! Detailed code can be found here. (https://github.com/hyunwoongko/transformer-pytorch)
What are some alternatives?
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
LaTeX-OCR - pix2tex: Using a ViT to convert images of equations into LaTeX code.
Transformers4Rec - Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.
attention-is-all-you-need-pytorch - A PyTorch implementation of the Transformer model in "Attention is All You Need".
scibert - A BERT model for scientific text.
how_attentive_are_gats - Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)
cuad - CUAD (NeurIPS 2021)
minGPT - A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training