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1 CLIP CLIP(Contrastive Language–Image Pre-training) 2 BLIP 3 BLIP 2 4 LLaVA 5 miniGPT 6 Instruction BLIP Reference 靠谱女士的组会分享［多模态大模型之clip，blip，blip–2， 阅读全文
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🥥 Table of Content 00 - Overview 01 - Tokenization 02 - Position Encoding 03 - Word Embedding 04 - Transformer Block(Attention + FFN) 05 - Model Head 阅读全文
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Resource:Sentence Embedding | 良睦路程序员 - Bilibili 阅读全文
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01 - Overview & Environments Step 1: Create a environment conda create -n transformers python==3.9.16 -y Step 2: Activate environment conda activate t 阅读全文
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1 Tensors 1.1 Create 1.自定义张量 最左边有几个括号，就是几维向量。 # 一维向量 X1 = torch.tensor([0.0, 1.0, 2.0]) # 二维向量 X2 = torch.tensor([[0., 1., 2.], [3., 4., 5.], [6., 7., 阅读全文
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🥥 Table of Content I. Probability II. Calculus 🥑 Get Started! I. Probability 01 - Conditional Probability & Joint Probaility 02 - Generative Model N 阅读全文
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1 RNNs 1.1 RNN(Recurrent Neural Netwrok) Resource 1: 用纸笔训练循环神经网络RNN Figure 1: RNN cell 1.2 Bi-RNN(Bidirectional Recurrent Neural Netwrok) 2 LSTMs 2.1 阅读全文
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Retrieval-Augmented Generation(RAG) 阅读全文
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0 Introduction Code: modeling_llama.py - hugging face transformers | GitHub What's new Rotary Position Embedding (RoPE) RMS Norm Grouped Query Attenti 阅读全文
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🥥 Table of Content 00 - Overview <1> Downstream Task 01 - Input Data Preprocessing <1> Tokenization & Dataset & DataLoader 03 - Fine Tune & Adapter < 阅读全文