tranquoctrinh

Aspect-Based-Sentiment-Analysis

Aspect Based Sentiment Analysis

Category-Classification

This is the model that categorizes which category a product_id belongs to. Using Efficientnet model combined with BERT.

FaceNet-HCMUS

Finetune-GPTJ

Fine-tune GPTJ for text generation task

huggingface-transformers-examples

Fine-tuning (or training from scratch) the library models for language modeling on a text dataset for GPT, GPT-2, ALBERT, BERT, DitilBERT, RoBERTa, XLNet... GPT and GPT-2 are trained or fine-tuned using a causal language modeling (CLM) loss while ALBERT, BERT, DistilBERT and RoBERTa are trained or fine-tuned using a masked language modeling (MLM) loss.

Image-Captioning-EfficientNet-Transformer

Image Captioning with Encoder as Efficientnet and Decoder as Decoder of Transformer combined with the attention mechanism.

transformer

This is a PyTorch implementation of the Transformer model in the paper Attention is All You Need

tranquoctrinh/transformer

This is a PyTorch implementation of the Transformer model in the paper Attention is All You Need

tranquoctrinh/Image-Captioning-EfficientNet-Transformer

Image Captioning with Encoder as Efficientnet and Decoder as Decoder of Transformer combined with the attention mechanism.

tranquoctrinh/Finetune-GPTJ

Fine-tune GPTJ for text generation task

tranquoctrinh/Aspect-Based-Sentiment-Analysis

Aspect Based Sentiment Analysis

tranquoctrinh/Category-Classification

This is the model that categorizes which category a product_id belongs to. Using Efficientnet model combined with BERT.

tranquoctrinh/FaceNet-HCMUS

tranquoctrinh/huggingface-transformers-examples

Fine-tuning (or training from scratch) the library models for language modeling on a text dataset for GPT, GPT-2, ALBERT, BERT, DitilBERT, RoBERTa, XLNet... GPT and GPT-2 are trained or fine-tuned using a causal language modeling (CLM) loss while ALBERT, BERT, DistilBERT and RoBERTa are trained or fine-tuned using a masked language modeling (MLM) loss.