實踐少樣本學習：GPT-Neo 與 🤗 Accelerated Inference API
Hugging Face Blog1,839 days agoTutorialIn the field of natural language processing (NLP), the emergence of GPT-3 demonstrated the tremendous power of "Few-shot Learning" — where a model only needs…
使用 Gradio 2.0 輕鬆部署與混合 Hugging Face 模型
Hugging Face Blog1,848 days agoReleaseIn May 2021, Gradio officially released version 2.0 and announced a deep integration with the Hugging Face platform. This collaboration fundamentally changed…
在 CPU 上擴展 BERT 推論效能（第一部分）
Hugging Face Blog1,883 days agoTutorialIn many real-world enterprise production environments, although GPUs offer extremely high throughput for deep learning inference, CPUs remain indispensable due…
使用 🤗 Transformers 與 Amazon SageMaker 進行分散式訓練：以 BART/T5 摘要生成模型為例
Hugging Face Blog1,895 days agoTutorialThis technical guide, published by Hugging Face in 2021, details how to use Amazon SageMaker's managed infrastructure and distributed training capabilities to…
Amazon SageMaker 與 Hugging Face 宣布深度合作：簡化企業級 NLP 模型訓練與部署★ 75
Hugging Face Blog1,911 days agoBusinessHugging Face has officially announced a deep partnership with Amazon Web Services (AWS), aimed at natively integrating the Hugging Face Transformers platform…
實戰分享：在 Google Cloud 上部署 Serverless Transformers Pipeline 的旅程
Hugging Face Blog1,916 days agoTutorialThis article is a hands-on experience report from the author on deploying a Hugging Face Transformers pipeline to a serverless environment on Google Cloud…
使用 🤗 Transformers 在 Hugging Face 中微調 Wav2Vec2 進行英文語音辨識 (ASR)★ 70
Hugging Face Blog1,922 days agoTutorialThis is a landmark technical tutorial published by the Hugging Face team in 2021, detailing how to fine-tune Meta AI's Wav2Vec2 model using the Hugging Face…
Hugging Face 讀書會：長文本 Transformer 模型技術解析與演進
Hugging Face Blog1,925 days agoCommentaryIn the field of natural language processing (NLP), the core of standard Transformer models (such as BERT and GPT-2) is the self-attention mechanism. However…
使用 Hugging Face Transformers 與 Ray 實現大規模檢索增強生成 (RAG)
Hugging Face Blog1,952 days agoTutorialRetrieval-Augmented Generation (RAG) is a powerful architecture that combines a "retriever" with a "generator." It enables language models to dynamically…
Hugging Face 支援 PyTorch / XLA：在 Google Cloud TPU 上加速 Transformer 模型訓練
Hugging Face Blog1,953 days agoReleaseHugging Face has announced a deep collaboration with Google Cloud, officially adding support for PyTorch/XLA within its ecosystem. The goal is to address the…
透過 DeepSpeed 與 FairScale 的 ZeRO 技術，讓 Hugging Face 訓練容納更多參數且速度更快★ 80
Hugging Face Blog1,974 days agoReleaseAs the parameter scale of Transformer models (such as GPT, T5, etc.) grows exponentially, deep learning faces a severe "Memory Wall" challenge. With limited…
Hugging Face 如何為 API 客戶將 Transformer 推理速度提升 100 倍
Hugging Face Blog1,975 days agoReleaseIn this technical blog post, the Hugging Face team reveals in detail how they achieved up to 100x speedup in inference for Transformer models for customers of…
將 Fairseq WMT19 翻譯系統移植至 Hugging Face Transformers
Hugging Face Blog2,051 days agoReleaseIn the field of natural language processing (NLP), machine translation has always been a core challenge. Facebook AI Research (FAIR) achieved outstanding…
Transformer 架構下的編碼器-解碼器（Encoder-Decoder）模型深度解析★ 70
Hugging Face Blog2,075 days agoTutorialThis classic blog post written by Hugging Face researcher Patrick von Platen takes a deep dive into the Transformer-based Encoder-Decoder model architecture…
如何生成文本：在 Transformers 中使用不同的解碼方法進行語言生成★ 85
Hugging Face Blog2,298 days agoTutorialThis classic technical blog post written by Hugging Face takes an in-depth look at how to select and tune different "decoding methods" when performing…
如何使用 Transformers 和 Tokenizers 從頭開始訓練新的語言模型★ 75
Hugging Face Blog2,314 days agoTutorialThis classic blog post from Hugging Face provides a detailed walkthrough of how to use their open-source ecosystem libraries — `transformers` and `tokenizers`…