使用 Sentence Transformers 訓練與微調嵌入模型 (Embedding Models)★ 80
Hugging Face Blog747 days agoReleaseThe official Hugging Face blog introduces a major update to the Sentence Transformers library (v3.0), centered on the launch of the new…
7 個你今天就能為應用程式加入的 AI 功能★ 75
Vercel Changelog766 days agoTutorialVercel has released a practical guide explaining how developers can use its powerful Vercel AI SDK to quickly add AI capabilities to existing web applications…
使用 Intel Gaudi 2 與 Intel Xeon 建構高性價比的企業級 RAG 應用★ 70
Hugging Face Blog766 days agoTutorialAs enterprise demand for Retrieval-Augmented Generation (RAG) technology surges, how to maintain high performance while controlling hardware costs has become…
Hugging Face 推出二進位與純量嵌入向量量化技術：大幅提升檢索速度並降低成本★ 85
Hugging Face Blog814 days agoTutorialAs RAG (Retrieval-Augmented Generation) and semantic search have become widespread, the maintenance costs of vector databases — especially RAM overhead — have…
使用 🤗 Optimum Intel 與 fastRAG 在 CPU 上實現最佳化嵌入向量生成★ 70
Hugging Face Blog821 days agoTutorialWhen building Retrieval-Augmented Generation (RAG) systems, converting large volumes of text into embeddings (vectors) is an indispensable and computationally…
🪆 Matryoshka 嵌入模型（俄羅斯套娃嵌入）入門介紹★ 85
Hugging Face Blog842 days agoTutorialThis article provides an in-depth introduction to Matryoshka Representation Learning (MRL), also known as Matryoshka embedding models. Traditional embedding…
Hugging Face 推出「企業情境排行榜」：專為真實世界應用設計的 LLM 評測基準★ 75
Hugging Face Blog865 days agoReleaseHugging Face has partnered with Patronus AI — a startup focused on LLM evaluation and defense — to officially launch the **Enterprise Scenarios Leaderboard**…
Hugging Face 推出「幻覺排行榜」，開源量化評估大型語言模型的幻覺率★ 75
Hugging Face Blog867 days agoReleaseWhile large language models (LLMs) have demonstrated remarkable generative capabilities across many domains, "hallucination" — where a model confidently…
如何建立自己的 Hugging Face 排行榜：以 Vectara 幻覺排行榜為例的完整指南★ 75
Hugging Face Blog884 days agoTutorialIn the open-source AI community, the Hugging Face Open LLM Leaderboard serves as an important benchmark for evaluating model capabilities. However, many…
使用開源模型進行更快、更便宜的文字嵌入 (Text Embeddings)
Replicate Blog947 days agoTutorialThis technical blog post from Replicate provides a detailed introduction to using the open-source BGE (BAAI General Embedding) model for efficient, low-cost…
使用 Hugging Face Inference Endpoints 輕鬆部署高效能嵌入模型★ 75
Hugging Face Blog964 days agoReleaseAs large language models (LLMs) and Retrieval-Augmented Generation (RAG) technology become increasingly widespread, embedding models have become an…
如何使用 ChromaDB 與 Mistral 實現檢索增強生成 (RAG)
Replicate Blog971 days agoTutorialThis technical blog post from Replicate provides a detailed walkthrough of how to build a basic Retrieval-Augmented Generation (RAG) application from scratch…
MTEB：海量文字嵌入基準測試（Massive Text Embedding Benchmark）正式推出★ 85
Hugging Face Blog1,334 days agoReleaseIn the field of natural language processing (NLP), text embeddings — the technique of converting text into real-valued vectors — are a foundational technology…
如何訓練與微調 Sentence Transformers 模型：Hugging Face 官方實戰指南★ 75
Hugging Face Blog1,404 days agoTutorialThis is a practical guide authored by Hugging Face, aimed at teaching developers how to train and fine-tune Sentence Transformers models to generate…
Hugging Face 向量嵌入（Embeddings）入門指南★ 75
Hugging Face Blog1,452 days agoTutorialThis classic blog post from Hugging Face is an essential introductory guide for understanding vector embeddings — the foundational technology underlying modern…
Hugging Face 釋出：如何用 10 億個訓練對訓練句子嵌入（Sentence Embedding）模型★ 75
Hugging Face Blog1,693 days agoTutorialThis classic Hugging Face blog post (co-authored by Sentence-Transformers creator Nils Reimers and others) provides a detailed account of how to train…
使用 Hugging Face Transformers 與 Ray 實現大規模檢索增強生成 (RAG)
Hugging Face Blog1,950 days agoTutorialRetrieval-Augmented Generation (RAG) is a powerful architecture that combines a "retriever" with a "generator." It enables language models to dynamically…