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Finetune: Scikit-learn Style Model Finetuning for NLP
Finetune is a library that allows users to leverage state-of-the-art pretrained NLP models for a wide variety of downstream tasks.
natural-language-processing finetuning pretraining transformers
Finetuning Transformers with JAX + Haiku
Walking through a port of the RoBERTa pre-trained model to JAX + Haiku, then fine-tuning the model to solve a downstream task.
jax haiku roberta transformers
Cycle Text-To-Image GAN with BERT
Image generation from their respective captions, building on state-of-the-art GAN architectures.
generative-adversarial-networks bert transformers image-to-text
A Survey of Long-Term Context in Transformers
Over the past two years the NLP community has developed a veritable zoo of methods to combat expensive multi-head self-attention.
transformers multi-head-attention attention natural-language-processing
Talking-Heads Attention
A variation on multi-head attention which includes linear projections across the attention-heads dimension, immediately before and after the softmax ...
multi-head-attention talking-heads-attention attention transformers
Custom Classifier on Top of Bert-like Language Model
Take pre-trained language model and build custom classifier on top of it.
bert language-modeling pytorch pytorch-lightning
Rethinking Batch Normalization in Transformers
We found that NLP batch statistics exhibit large variance throughout training, which leads to poor BN performance.
power-normalization batch-normalization transformers natural-language-processing
Visual Paper Summary: ALBERT(A Lite BERT)
An illustrated summary of ALBERT paper and how it improves BERT and makes it resource efficient
albert bert transformers natural-language-processing
Using Different Decoding Methods for LM with Transformers
A look at different decoding methods for generate subsequent tokens in language modeling.
language-modeling decoder transformers huggingface
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