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abelrguezr
Perfil de creador de GitHub

abelrguezr

Vista por repositorio de 908 skills recopiladas en 1 repositorios de GitHub.

skills recopiladas
908
repositorios
1
actualizado
23 mar 2026
explorador de repositorios

Repositorios y skills representativas

ai-fuzzing-assistant
Analistas de seguridad de la información

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 mar 2026
burp-mcp-integration
Analistas de seguridad de la información

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 mar 2026
deep-learning-helper
Científicos de datos

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 mar 2026
llm-fundamentals
Profesores de ciencias de la computación, postsecundario

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 mar 2026
text-tokenizer
Científicos de datos

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 mar 2026
llm-data-sampling
Científicos de datos

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 mar 2026
token-embeddings
Desarrolladores de software

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 mar 2026
attention-mechanisms
Científicos de datos

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 mar 2026
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