transfer-learning

A curated list of NLP resources focused on Transformer networks, attention mechanism, GPT, BERT, ChatGPT, LLMs, and transfer learning.

AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.

[MICCAI 2019 Young Scientist Award] [MEDIA 2020 Best Paper Award] Models Genesis, one of the first "foundation" models in medical image analysis for multiple downstream tasks

Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem. ⭐ Star to support our work!

Paper List of Pre-trained Foundation Recommender Models

Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.

Reproducible scaling laws for contrastive language-image learning (https://arxiv.org/abs/2212.07143)

Curso práctico: NLP de cero a cien 🤗

The "tl;dr" on a few notable transformer papers (pre-2022).

[TPAMI 2023] Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification

autoupdate paper list

BERT 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.

Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and Topic Models.

Open Toolkit for Painless Object Detection

Wav2Keyword is keyword spotting(KWS) based on Wav2Vec 2.0. This model shows state-of-the-art in Speech commands dataset V1 and V2.

Applying NLP transfer learning techniques to predict Tweet stance toward a topic

[ICLR 2024] This is the repository for the paper titled "DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning"

Implementation of Logistic Regression, MLP, CNN, RNN & LSTM from scratch in python. Training of deep learning models for image classification, object detection, and sequence processing (including transformers implementation) in TensorFlow.

Tensorflow and Keras implementation of the state of the art researches in Dialog System NLU

SciFive: a text-text transformer model for biomedical literature