There are 16 repositories under language-modeling topic.
Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates.
Plug and Play Language Model implementation. Allows to steer topic and attributes of GPT-2 models.
Keras implementation of BERT with pre-trained weights
A Modern C++ Data Sciences Toolkit
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
INTERSPEECH 2023-2024 Papers: A complete collection of influential and exciting research papers from the INTERSPEECH 2023-24 conference. Explore the latest advances in speech and language processing. Code included. Star the repository to support the advancement of speech technology!
End-to-end ASR/LM implementation with PyTorch
Benchmarking long-form factuality in large language models. Original code for our paper "Long-form factuality in large language models".
This repository contains a collection of papers and resources on Reasoning in Large Language Models.
ICASSP 2023-2024 Papers: A complete collection of influential and exciting research papers from the ICASSP 2023-24 conferences. Explore the latest advancements in acoustics, speech and signal processing. Code included. Star the repository to support the advancement of audio and signal processing!
Efficient Python library for Extended LSTM with exponential gating, memory mixing, and matrix memory for superior sequence modeling.
An Extensible Continual Learning Framework Focused on Language Models (LMs)
An implementation of DeepMind's Relational Recurrent Neural Networks (NeurIPS 2018) in PyTorch.
Curso práctico: NLP de cero a cien 🤗
Lyrics Generator aka Character-level Language Modeling with Multi-layer LSTM Recurrent Neural Network
Independently Recurrent Neural Networks (IndRNN) implemented in pytorch.
Use tensorflow's tf.scan to build vanilla, GRU and LSTM RNNs
Comparatively fine-tuning pretrained BERT models on downstream, text classification tasks with different architectural configurations in PyTorch.
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology. (DEPRECATED)
Neural Networks for Protein Sequence Alignment
Training an n-gram based Language Model using KenLM toolkit for Deep Speech 2
Implementation of Gated State Spaces, from the paper "Long Range Language Modeling via Gated State Spaces", in Pytorch
Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"
Full finetuning of large language models without large memory requirements