06: Learning Transferable Visual Models From Natural Language Supervision (
CLIP
)
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📝 100 AI Papers with Code
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Transformer
Vision Transformer
🎓 Stanford CS336: LLM from Scratch
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Lecture 01: Introduction & BPE
Lecture 02: PyTorch Basics & Resource Accounts
Lecture 03: Transformer LM Architecture
Lecture 04: MoE Architecture
Lecture 05&06: GPU Optimization, Triton & FlashAttention
Lecture 07&08: Parallelism
Lecture 09&11: Scaling Laws
Lecture 10: Inference & Deployment
Lecture 12: Evaluation
Lecture 13&14: Data Collection & Processing
Lecture 15: LLM Alignment SFT & RLHF(PPO, DPO)
Lecture 16 & 17: LLM Alignment SFT & RLVR(GRPO)
Assignment 01: BPE Tokenizer & Transformer LM
Assignment 02: Flash Attention & Parallelism
Assignment 05: SFT & GRPO
📖 Deep Learning Foundation & Concepts
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1
Preliminary
2
CLIP
3
Summary
4
Key Concepts
5
Q & A
6
Related resource & Further Reading
06: Learning Transferable Visual Models From Natural Language Supervision (
CLIP
)
Multi Modality
Representation Learning
一种通过对齐图像与自然语言文本的对比学习框架，在海量图文对上训练统一表示，从而获得强零样本泛化能力的视觉模型。
1
Preliminary
2
CLIP
3
Summary
4
Key Concepts
5
Q & A
6
Related resource & Further Reading
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