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acm.14.lab1

acm.14.lab2

acm.14.lab3

albert

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

albert-chinese-ner

使用预训练语言模型ALBERT做中文NER

albert-pytorch

Pytorch Implementation of ALBERT(A Lite BERT for Self-supervised Learning of Language Representations)

albert-tf

TensorFlow code for a lite bert reimplementation

awesome-rlhf

A curated list of reinforcement learning with human feedback resources (continually updated)

categoricalencodingbenchmark

Benchmarking different approaches for categorical encoding for tabular data

cft-challenge-2018

CNN and GRU spellchecker

cft2018-fiotypos

commonsense-dialogues

A crowdsourced dataset of dialogues grounded in social contexts involving utilization of commonsense.

course_ml

Курс "Машинное обучение в R, Python и H2O"

deepnlp-course

Deep NLP Course

electra

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

facebook-hateful-memes

Facebook hateful memes challenge using multi-modal learning. More info about it here: https://ai.facebook.com/blog/hateful-memes-challenge-and-data-set

fnet-tensorflow

Tensorflow Implementation of "FNet: Mixing Tokens with Fourier Transforms."

fnet-tensorflow-pytorch

TensorFlow & PyTorch implementation of the paper "FNet: Mixing Tokens with Fourier Transforms".

fred-t5-finetuning

Скрипт для файнтюна FRED-T5

gated-cnn-s-using-keras

A Python class that implements a Gated CNN using Keras with TensorFlow backend.

gpt-4-llm

hatexplain

Can we use explanations to improve hate speech models? Our paper accepted at AAAI 2021 tries to explore that question.

jax-in-action

Notebooks for the "JAX in Action" book

keras-tcn

Keras Temporal Convolutional Network.

keras_attentivenormalization

Unofficial Keras implementation of the paper Attentive Normalization.

labse

Language-agnostic BERT Sentence Embedding (LaBSE)

llama2

This repository contains an implementation of the LLaMA 2 (Large Language Model Meta AI) model, a Generative Pretrained Transformer (GPT) variant. The implementation focuses on the model architecture and the inference process. The code is restructured and heavily commented to facilitate easy understanding of the key parts of the architecture.

lm-finetune

Код для файнтюна LM (rugpt, LLaMa, FRED T5) средствами transformers + deepspeed + LoRa

lm-human-preferences--tf

Code for the paper Fine-Tuning Language Models from Human Preferences

machine-learning-with-python

Practice and tutorial-style notebooks covering wide variety of machine learning techniques