機器學習即程式碼（ML as Code）的時代已經到來：Hugging Face 談開發者導向的 AI 新典範
Hugging Face Blog1,699 days agoOpinionThis classic 2021 article from Hugging Face declared the official arrival of the "Machine Learning as Code" (ML as Code) era. The central argument is that…
在 Hugging Face Spaces 上使用 Streamlit 託管您的模型與資料集★ 70
Hugging Face Blog1,714 days agoNew ToolHugging Face has announced the launch of its new "Spaces" feature, designed to provide the machine learning community with a simple, fast, and free platform…
Hugging Face 與 Graphcore 達成合作，推出針對 IPU 優化的 Transformers 模型
Hugging Face Blog1,735 days agoReleaseIn September 2021, Hugging Face, the leading open-source AI community, and British AI chip design company Graphcore announced a strategic partnership aimed at…
網際網路上的深度學習：以協作方式訓練語言模型
Hugging Face Blog1,796 days agoReleaseIn the field of artificial intelligence, training large language models (LLMs) has always been an extremely resource-intensive task. Traditionally, this…
Sentence Transformers 正式整合至 Hugging Face Hub
Hugging Face Blog1,813 days agoReleaseHugging Face officially announced a deep integration with the highly popular open-source library `sentence-transformers`. `sentence-transformers` (commonly…
深入理解 BigBird 的區塊稀疏注意力機制 (Block Sparse Attention)
Hugging Face Blog1,902 days agoTutorialTraditional Transformer models (such as BERT) are constrained by the quadratic complexity $O(N^2)$ of their self-attention mechanism, and are typically limited…
使用 🤗 Transformers 在 Hugging Face 中微調 Wav2Vec2 進行英文語音辨識 (ASR)★ 70
Hugging Face Blog1,921 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 Blog1,924 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…
建構華麗神經網路的實用指南：給開發者的幾個簡單建議
Hugging Face Blog1,936 days agoOpinionThis classic blog post from Hugging Face explores the common mistakes developers make when building complex (fancy) neural networks, and the simple principles…
Hugging Face Transformers 中的 TensorFlow 模型加速與 TF Serving 部署指南
Hugging Face Blog1,966 days agoTutorialWhen deploying Transformer models in production environments, latency and throughput are often the deciding factors for a project's success. Hugging Face…
利用預訓練語言模型權重「熱啟動」Encoder-Decoder 模型
Hugging Face Blog2,044 days agoTutorialIn the field of natural language processing (NLP), sequence-to-sequence (Seq2Seq) models — such as those used for translation or summarization — typically…
將 Fairseq WMT19 翻譯系統移植至 Hugging Face Transformers
Hugging Face Blog2,050 days agoReleaseIn the field of natural language processing (NLP), machine translation has always been a core challenge. Facebook AI Research (FAIR) achieved outstanding…
使用 Transformers 與 Ray Tune 進行超參數搜尋
Hugging Face Blog2,051 days agoTutorialThis classic article from the official Hugging Face blog provides a detailed guide on how to integrate Hugging Face's `Transformers` library with the powerful…
Transformer 架構下的編碼器-解碼器（Encoder-Decoder）模型深度解析★ 70
Hugging Face Blog2,074 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…
使用區塊稀疏矩陣（Block Sparse Matrices）打造更小、更快的語言模型
Hugging Face Blog2,104 days agoTutorialIn the field of natural language processing (NLP), the Transformer architecture has become the dominant paradigm, but its core self-attention mechanism…
Reformer：挑戰語言模型長文本處理極限的架構
Hugging Face Blog2,173 days agoPaperThis technical blog post published by Hugging Face takes a deep dive into how the Reformer architecture overcomes the memory and computational bottlenecks that…