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abelrguezr
GitHub 제작자 프로필

abelrguezr

1개 GitHub 저장소에서 수집된 908개 skills를 저장소 단위로 보여줍니다.

수집된 skills
908
저장소
1
업데이트
2026년 3월 23일
저장소 탐색

저장소와 대표 skills

ai-fuzzing-assistant
정보 보안 분석가

AI-assisted fuzzing and vulnerability discovery. Use this skill whenever the user wants to generate fuzzing seeds, evolve grammars, analyze crashes, create proof-of-vulnerability exploits, or generate patches for discovered bugs. Trigger on mentions of…

2026년 3월 23일
burp-mcp-integration
정보 보안 분석가

Set up and use Burp Suite's MCP Server extension to enable LLM-assisted passive vulnerability discovery. Use this skill whenever the user wants to integrate Burp with MCP-capable AI tools (Codex, Gemini, Ollama, Claude), configure the MCP proxy, troubleshoot…

2026년 3월 23일
deep-learning-helper
데이터 과학자

Help users understand and implement deep learning concepts including neural networks, CNNs, RNNs, LLMs, and diffusion models. Use this skill whenever the user asks about deep learning architectures, wants to build neural networks in PyTorch, needs help with…

2026년 3월 23일
llm-fundamentals
고등교육 컴퓨터공학 교원

Explain and teach Large Language Model fundamentals including pretraining, model architecture, PyTorch tensors, automatic differentiation, and backpropagation. Use this skill whenever the user asks about LLM concepts, neural network training, PyTorch…

2026년 3월 23일
text-tokenizer
데이터 과학자

How to tokenize text for LLMs and NLP models. Use this skill whenever the user needs to convert text into token IDs, understand tokenization methods (BPE, WordPiece, Unigram), work with vocabularies, or implement tokenization for machine learning. Make sure…

2026년 3월 23일
llm-data-sampling
데이터 과학자

How to prepare and sample text data for training large language models. Use this skill whenever the user mentions data preparation, tokenization, sliding windows, sequence generation, training data, LLM datasets, or needs to create input/target pairs for…

2026년 3월 23일
token-embeddings
소프트웨어 개발자

Create and work with token embeddings for LLMs. Use this skill whenever you need to understand token embeddings, create embedding layers in PyTorch, add positional embeddings (absolute, relative, or RoPE), or debug embedding-related issues in your language…

2026년 3월 23일
attention-mechanisms
데이터 과학자

How to implement and understand attention mechanisms in neural networks and LLMs. Use this skill whenever the user needs to build self-attention layers, causal attention, multi-head attention, or understand how attention weights are calculated. Trigger this…

2026년 3월 23일
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