Reading Literature 1: Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training (article translation and its own understanding and summary) - Code World

Reading Literature 1: Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training (article translation and its own understanding and summary)

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Origin blog.csdn.net/m0_51440939/article/details/124924329

Reading Literature 1: Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training (article translation and its own understanding and summary)

Чтение литературы 1: Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training (перевод статьи, ее собственное понимание и краткое изложение)

Literatur lesen 1: Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training (Übersetzung des Artikels und eigenes Verständnis und Zusammenfassung)

Literatura de lectura 1: Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training (traducción del artículo y su propia comprensión y resumen)

Literatura de leitura 1: Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training (tradução do artigo e seu próprio entendimento e resumo)

【论文笔记】BLIP: Bootstrapping Language-Image Pre-training forUnified Vision-Language Understanding and

文献を読む 1: Bootstrapping ViTs: Towards Liberation Vision Transformers from Pre-training (記事の翻訳とその独自の理解と要約)

Intensive reading of Li Mu's paper: BERT "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding"

[NLP classic paper intensive reading] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Transformers pre-training model uses: translation Translation

[Notes] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Transformers pre-training model uses: Text Summary Summarization

【论文笔记】BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

[Natural Language Processing | BERT] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Paper Explanation

[Paper Notes] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

[Intensive reading of NLP classic papers] Improving Language Understanding by Generative Pre-Training

LIO-SAM runs its own dataset from 0 to 1

Entwicklung und Evaluierung von VLP (Vision-Language Pre-training) (1)

Cross-modal retrieval paper reading: Multi-Grained Vision Language Pre-Training: Aligning Texts with VisualConcepts(X-VLM)

Cross-modal retrieval paper reading: (PTP)Position-guided Text Prompt for Vision-Language Pre-training

Graph convolution literature reading 1

【论文笔记】GPT-1：Improving Language Understanding by Generative Pre-Training

GPT1解读：Improving Language Understanding by Generative Pre-Training

Re45：读论文 GPT-1 Improving Language Understanding by Generative Pre-Training

In-depth understanding of deep learning - BERT (Bidirectional Encoder Representations from Transformers): model summary and precautions

"From 0-1" - reading summary

Build Vision Transformers (tensorflow version) from scratch

Build Vision Transformers from scratch (Pytorch version)

Article reading summary: GPT

From 0 to 1: How to build a large-scale multilingual code generation pre-training model

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