AdaSeq: An All-in-One Library for Developing State-of-the-Art Sequence Understanding Models
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Updated
Nov 15, 2023 - Python
AdaSeq: An All-in-One Library for Developing State-of-the-Art Sequence Understanding Models
A Simple but Powerful SOTA NER Model | Official Code For Label Supervised LLaMA Finetuning
Transformer-based models implemented in tensorflow 2.x(using keras).
Code and data form the paper BERT Got a Date: Introducing Transformers to Temporal Tagging
A collection of datasets for Ukrainian language
Token classification using Phobert Models for Vietnamese
The MERIT Dataset is a fully synthetic, labeled dataset created for training and benchmarking LLMs on Visually Rich Document Understanding tasks. It is also designed to help detect biases and improve interpretability in LLMs, where we are actively working. This repository is actively maintained, and new features are continuously being added.
Implementation of the paper, MAPLE - MAsking words to generate blackout Poetry using sequence-to-sequence LEarning, ICNLSP 2021
Applied Deep Learning 深度學習之應用 by Vivian Chen 陳縕儂 at NTU CSIE
Data and code for the paper "ID10M: Idiom Identification in 10 Languages" (NAACL 2022).
Labeled Russian text token-by-token for training models for NER task based samples got from parsing different resources and generated by ChatGPT.
MAPLEv2 - Multi-task Approach for generating blackout Poetry with Linguistic Evaluation
Data pipelines for both TensorFlow and PyTorch!
summer internship project @ JetBrains Research
Scrap, token classification and model deployment for a selective process.
Keyword extraction to automate the discovery of dataset in publications and public reports
This repo provides scripts for fine-tuning HuggingFace Transformers, setting up pipelines and optimizing token classification models for inference. They are based on my experience developing a custom chatbot, I’m sharing these in the hope they will help others to quickly fine-tune and use models in their projects! 😊
A webapp built using Gradio for demonstrating the capabilities of the Spacy NER pipeline.
API for Yoda-NER and Yoda-FITS model. NLP models for Google Feed product optimization
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