Скачать или смотреть "Transformers" - from "It's AIght: Required Learning for Data Scientists"

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[Intro: Fast Spoken Rap, building momentum]
Yo, step into the matrix, attention is the key,
Transformers changed the game – let me break it down, see!
From Vaswani '17, "Attention Is All You Need,"
Self-attention revolution, plantin' the seed.
[Verse 1: Rapid Fire Rap]
Stacked encoder-decoder, but GPT flipped the script,
Decoder-only architecture, autoregressive grip.
Tokens hit the embeddin', vector space we live in,
Vocab size massive, positional sin begin.
Learnable embeddings map words to dense floats,
D-model 512 up to thousands – heavy boats.
Add positional encodin', sine waves or RoPE,
Order matters now, no more bag-of-words cope.
Feed-forward layers, GELU or SwiGLU fire,
Layer norm stabilizin', takin' it higher.
[Chorus: Explosive Rapid Hook]
Transformers! Embeddings! Powerin' the brain!
Attention heads alignin', scalin' through the pain!
Context window growin', billions in the mix,
From BERT to GPT – watch the paradigm shift!
Embeddings dense and rich, meanin' in the vec,
Self-attention scalin' – what you gonna check next?
[Verse 2: Accelerating Technical Bars]
Multi-head attention, queries keys and values split,
Scaled dot-product magic, relevance they hit.
Q times K transpose, softmax on the scores,
Value matrix weighted – openin' the doors.
Parallel heads learn different subspaces quick,
Concat and project – thick representation trick.
Residual connections, skip around the block,
Gradient flow preserved, no vanishin' shock.
Token embeddings + position + segment type,
Contextual vectors ripe for the hype.
[Verse 3: High-Speed Flow]
Pre-train on next token, masked LM for BERT,
Bidirectional power, representation alert.
Fine-tune downstream, GLUE tasks they slay,
Transfer learnin' era – leadin' the way.
Embeddin' space magic, cosine similarity,
Semantic neighbors cluster, proximity clarity.
King minus man plus woman ≈ queen in the zone,
Analogies emergin' from the vectors alone.
Rotary embeddings, absolute gone relative flow,
Longer contexts handled, extrapolation grow.
[Bridge: Intense Spoken Rap, brief slowdown then explode]
FlashAttention, KV cache, inference optimized speed,
Sparse mixtures of experts – scalin' what we need.
From 117M params to trillions in the game,
Embeddings gettin' deeper, but the core stays the same.
[Verse 4: Peak Velocity Bars]
Context length explosion, 128k, million soon come,
Ring attention, sliding windows – never feelin' numb.
Retrieval augmented, embeddings in the store,
Vector DB lookup, relevant chunks galore.
Contrastive trainin', sentence embeddings tight,
All-MiniLM-L6, efficiency in sight.
Multimodal now – CLIP joinin' the fray,
Image and text aligned in the same embed space play.
[Chorus: Final Massive Hook, layered echoes]
Transformers! Embeddings! Runnin' every LLM!
Attention mechanism – the ultimate gem!
Dense vectors capturin' meaning and relation,
Powerin' the models of this generation!
Transformers! Embeddings! Future lookin' bright,
Self-attention forever – we own the night!
[Outro: Frenzied Rap Fade]
Yo, from attention paper to frontier models tall,
Embeddings and transformers – they conquer it all!
Neural nets evolvin', next paradigm call...
But right now we ridin' this wave – stand proud and tall!