Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
$ git clone https://github.com/backprop-ai/backprop.gitBERT classification model for processing texts longer than 512 tokens. Text is first divided into smaller chunks and after feeding them to BERT, intermediate results are pooled. The implementation allows fine-tuning.
An implementation of the BERT model and its related downstream tasks based on the PyTorch framework. @θ·ζε¦ζΊε¨ε¦δΉ
Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
倧θ§ζ¨‘δΈζθͺηΆθ―θ¨ε€ηθ―ζ Large Scale Chinese Corpus for NLP
Pre-training of Deep Bidirectional Transformers for Language Understanding: pre-train TextCNN
This repo contains a PyTorch implementation of a pretrained BERT model for multi-label text classification.
Data from GitHub Β· snapshot Sep 24, 2026