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Vyacheslav EfimovinTowards Data ScienceLarge Language Models: TinyBERT — Distilling BERT for NLPUnlocking the power of Transformer distillation in LLMsOct 21, 2023Oct 21, 2023
A.S. ReisfieldComparing Media of Art: Perfume Wins AgainThere is no art left to create. There are no isms of art left unclaimed. Possibilities to recycle used fragments, they’re exhausted. The…Apr 2Apr 2
Victor SanhinHuggingFace🏎 Smaller, faster, cheaper, lighter: Introducing DilBERT, a distilled version of BERTYou can find the code to reproduce the training of DilBERT along with pre-trained weights for DilBERT here.Aug 28, 201920
Vyacheslav EfimovinTowards Data ScienceLarge Language Models: TinyBERT — Distilling BERT for NLPUnlocking the power of Transformer distillation in LLMsOct 21, 2023
A.S. ReisfieldComparing Media of Art: Perfume Wins AgainThere is no art left to create. There are no isms of art left unclaimed. Possibilities to recycle used fragments, they’re exhausted. The…Apr 2
Aaditya uraQuantization vs Distillation in Neural Networks: A ComparisonA dive into the techniques of quantizing and distilling deep learning models: What are they and how do they differ?Nov 11, 2023
Igor NovikovinDataDrivenInvestorTremendously increasing models performance using distillationHave you ever wondered if a human brain has limited capacity and you can learn that damn English because you remember too many Pokemons? Or…Mar 14
Remi Ouazan ReboulinTowards Data ScienceDistillation of BERT-like models: the codeHow to implement DistilBERT’s method to distill any BERT-like modelJan 24, 20222