transformer
CommunityUnderstand and implement Transformer architectures for sequence modeling.
Software Engineering#self-attention#transformer#sequence modeling#positional encoding#multi-head attention#FFN
Authorhung-phan
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides a comprehensive reference and guide to Transformer architectures, helping users understand their components and how to implement them for various sequence modeling tasks.
Core Features & Use Cases
- Transformer Architecture Reference: Offers a detailed explanation of the Transformer architecture, including self-attention, multi-head attention, positional encodings, FFN variants, layer normalization, and more.
- Implementation Guidance: Provides code examples and explanations for implementing various Transformer components.
- Use Case: Ideal for researchers, developers, and engineers working on sequence-to-sequence tasks such as translation, summarization, and NLP applications.
Quick Start
Explore the Transformer architecture details by reading the 'transformer' skill's SKILL.md file.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 Claude Code Installation
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Please help me install this Skill: Name: transformer Download link: https://github.com/hung-phan/ml-skills/archive/main.zip#transformer Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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