Huggingface Transformers

Creator
Creator
Seonglae ChoSeonglae Cho
Created
Created
2023 May 3 17:8
Editor
Edited
Edited
2026 Feb 13 19:23
Refs
Huggingface Transformers Usages
 
 
Huggingface Transformers Addons
 
 
 
 

Standardize, Don’t Abstract

This explains the design principles (
Tenet
s) and recent engineering changes that make 1M+ Python LOC and 400+ model architectures "maintainable despite continuous additions." transformers aims to be the Source of Truth for each model implementation, prioritizing performance and reproducibility. Since users are mostly researchers/power users, code is the 'product' and must be easy to read, debug, and modify.
Standardize, Don't Abstract: only commonize infrastructure, keep model semantics inside model files. DRY*: deduplication isn't always good (
DRY Principle
* (DO Repeat Yourself). Strategic duplication is allowed for user readability and local semantics. The essence is: "Keep model seantics transparent in one file (for readability/hackability), while reducing maintenance burden through modular definitions and config-based composition."
huggingface.co
🤗 Transformers
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
🤗 Transformers
SimpleTransformers: 알기 쉬운 트랜스포머
이 섹션에서, Hugging Face API를 사용해 간단한 감성 분류기를 구축해보겠습니다. IMDB 데이터세트를 사용해 Distil BERT 모델을 미세 조정하겠습니다. Hugging Face 트랜스포머를 사용해 단 몇 줄의 코드로 감성 분류기를 구축할 수 있습니다. 하지만 여기에는, 특히 트랜스포머를 막 시작한 분들의 경우, 몇 가지 까다로운 부분이 있습니다. 1.. 불러오기(Imports) 트랜스포머마다 다른 불러오기(imports)가 필요합니다.
SimpleTransformers: 알기 쉬운 트랜스포머
Models
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Models
 
 
 

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