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abelrguezr
Profil créateur GitHub

abelrguezr

Vue par dépôt de 908 skills collectés dans 1 dépôts GitHub.

skills collectés
908
dépôts
1
mis à jour
23 mars 2026
explorateur de dépôts

Dépôts et skills représentatifs

ai-fuzzing-assistant
Analystes en sécurité de l'information

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 mars 2026
burp-mcp-integration
Analystes en sécurité de l'information

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 mars 2026
deep-learning-helper
Scientifiques des données

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 mars 2026
llm-fundamentals
Enseignants en informatique, postsecondaire

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 mars 2026
text-tokenizer
Scientifiques des données

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 mars 2026
llm-data-sampling
Scientifiques des données

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 mars 2026
token-embeddings
Développeurs de logiciels

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 mars 2026
attention-mechanisms
Scientifiques des données

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 mars 2026
Affichage de 8 skills collectés sur 908.
1 dépôts affichés sur 1
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