Github repo with tutorials to fine tune transformers for diff NLP tasks
A flexible, adaptive classification system for dynamic text classification
Transformers 3rd Edition
An all-in-one AI audio playground using Cloudflare AI Workers to transcribe, analyze, summarize, and translate any audio file.
Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.
Sentiment analysis neural network trained by fine-tuning BERT, ALBERT, or DistilBERT on the Stanford Sentiment Treebank.
Build and train state-of-the-art natural language processing models using BERT
Pytorch-Named-Entity-Recognition-with-transformers
Simple State-of-the-Art BERT-Based Sentence Classification with Keras / TensorFlow 2. Built with HuggingFace's Transformers.
Tensorflow and Keras implementation of the state of the art researches in Dialog System NLU
Multi-Class Text Classification for products based on their description with Machine Learning algorithms and Neural Networks (MLP, CNN, Distilbert).
A collection of resources on using BERT (https://arxiv.org/abs/1810.04805 ) and related Language Models in production environments.
Distillation of BERT model with catalyst framework
FoodBERT: Food Extraction with DistilBERT
DistilBERT model pre-trained on 131 GB of Japanese web text. The teacher model is BERT-base that built in-house at LINE.
Topic clustering library built on Transformer embeddings and cosine similarity metrics.Compatible with all BERT base transformers from huggingface.
Aura is an emotion-aware music recommender that understands your mood from natural language input. It uses a fine-tuned BERT model trained on the GoEmotions dataset to detect your emotion. Based on the emotion, Aura suggests a song to comfort your mood or celebrate it through music.
Task Complexity Classifier using Transformer-based NLP model based on Bloom's Taxonomy
Compares the DistilBERT and MobileBERT architectures for mobile deployments.
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