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abelrguezr
GitHub-Creator-Profil

abelrguezr

Repository-Ansicht von 908 gesammelten Skills in 1 GitHub-Repositories.

gesammelte Skills
908
Repositories
1
aktualisiert
23. März 2026
Repository-Explorer

Repositories und repräsentative Skills

ai-fuzzing-assistant
Informationssicherheitsanalysten

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…

23. März 2026
burp-mcp-integration
Informationssicherheitsanalysten

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…

23. März 2026
deep-learning-helper
Datenwissenschaftler

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…

23. März 2026
llm-fundamentals
Hochschullehrer für Informatik

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…

23. März 2026
text-tokenizer
Datenwissenschaftler

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…

23. März 2026
llm-data-sampling
Datenwissenschaftler

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…

23. März 2026
token-embeddings
Softwareentwickler

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…

23. März 2026
attention-mechanisms
Datenwissenschaftler

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…

23. März 2026
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