AI & LLM

Models, prompts, tokens, embeddings, evaluation, safety

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model17 inference27 prompt11 token7 context3 embedding7 training26 evaluation16 safety8 multimodal13

model

17

base-model depth diffusion instruct-model llm model model-add model-alert model-check model-deploy model-download model-off model-swap model-weights reasoning-model small-language-model transformer

inference

27

attention attention-head batch-inference beam-search confidence decoder greedy inference inference-batch inference-fast kv-cache latency llm-chat logits logprobs parameters retry sampling self-consistency softmax speculative-decode streaming-response structured-output temperature throughput top-p tree-of-thought

prompt

11

chain-of-thought few-shot instruction prompt prompt-chain prompt-library prompt-stuffing prompt-template system-prompt user-prompt zero-shot

token

7

cost-per-token token token-cost token-count token-limit token-usage tokenizer

context

3

context-compress context-full context-window

embedding

7

dimension distance embedding-model embedding-space encoder similarity vector

training

26

adapter alignment checkpoint dataset distil dpo early-stop epoch fine-tune fine-tuning gradient learning-rate loss loss-curve noise normalize optimiser overfit pretrain prune quantization regularise rlhf training training-data underfit

evaluation

16

ablation accuracy benchmark best-of-n confusion-matrix degradation drift eval-suite evaluation f1 golden-set human-eval model-comparison perplexity precision reward-model

safety

8

bias bias-check content-filter guardrail hallucination refusal safety-check toxicity

multimodal

13

audio-gen audio-model denoise image-gen image-generation multimodal ocr pose speech speech-to-text text-to-speech video-gen vision-model

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135 AI & LLM icons in outline and duotone at three weights, generated from one grid so nothing in the set can drift out of step. MIT licensed — commercial use, no attribution, no seat count.

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