Swift Core ML 3 Implementations of GPT-2 and Bert
GitHub - huggingface/swift-coreml-transformers: Swift Core ML 3 implementations of GPT-2, DistilGPT-2, BERT, and DistilBERT for Question answering. Other Transformers coming soon!
This repo is not actively maintained and has been archived. For an in-development replacement, please head over to swift-transformers!
Swift Core ML implementations of Transformers: GPT-2, DistilGPT-2, BERT, DistilBERT, more coming soon!
This repository contains:

For BERT and DistilBERT:

pretrained Google BERT and Hugging Face DistilBERT models fine-tuned for Question answering on the SQuAD dataset.
Swift implementations of the BERT tokenizer (BasicTokenizer and WordpieceTokenizer) and SQuAD dataset parsing utilities.
A neat demo question answering app.


For GPT-2 and DistilGPT-2:

a conversion script from PyTorch trained GPT-2 models (see our transformers repo) to CoreML models.
The GPT-2 generation model itself, including decoding strategies (greedy and TopK are currently implemented) and GPT-2 Byte-pair encoder and decoder.
A neat demo app showcasing on-device text generation.



🦄 GPT-2 and DistilGPT-2
Unleash the full power of text generation with GPT-2 on device!!

🐸 BERT and DistilBERT
The BERTSQUADFP16 Core ML model was packaged by Apple and is linked from the main ML models page. It was demoed at WWDC 2019 as part of the Core ML 3 launch.
The DistilBERT Core ML models were converted from 🤗/transformers exports using the scripts in this repo.

🦄 Demo Time 🔥

Apple demo at WWDC 2019

full video here
BERT Architecture (wwdc slide)

Notes
We use git-lfs to store large model files and it is required to obtain some of the files the app needs to run.
See how to install git-lfson the installation page
