This is the repository holding code and data for "FrugalML: How to Use ML Prediction APIs More Accurately and Cheaply".

A named entity recognition system that is flexible and domain-independent by generating labels based on confidence scores. The model, a finetuned Roberta, can identify potential named entities and be customized to fit the needs of various tasks and applications through monitoring and fine-tuning. A Flask app is provided for visualisation.

Apply prompt learning in Chinese NER tasks

Contains sequence-model implementations of on and off-policy imitation learning algorithms for problems with unobserved contexts.

cooking some neural nets

[NeurIPS 2022 Workshop] A Case Study with Negated Prompts using T0 (3B, 11B), InstructGPT (350M-175B), GPT-3 (350M - 175B) & OPT (125M - 175B) LMs

News Authentication Via Emotion

[ICLR 2022] Towards Continual Knowledge Learning of Language Models

Text Generator for Amazon Ads. Use Natural Language Generation (NLG) technology to auto-generate text. Fine-tuning of pre-trained gpt-neo models to improve upon the RNN LSTM model

Improving Text-to-Image Models with Large Language Models

Code that accompanies the PyData New York (2022) talk: Addressing the sensitivity of Large language models

Deploy KoGPT with Triton Inference Server

Experimental search engine for conversational AI such as parl.ai, large language models such as OpenAI GPT3, and humans (maybe).

Text sentiment analysis using large language models, served via REST API built with Flask

Benchmark XGBoost against Large Language Models on IMDB 50K Movie Dataset

Pre-training and fine-tuning experiments with T5

Let's finetune BLOOM-3B on Pile of Law - r/legal_advice

Bonan & Samo. January 2023. Paper on cross-linguistic bias in health-related content in Transformer-based language models.

Majority of the Large Language Models summarized in a table. From the original Transformer to ChatGPT and beyond.