Hugging Face 釋出 Accelerate 1.0.0 正式版：邁向分散式訓練與大模型推理的全新里程碑★ 80
Hugging Face Blog639 days agoReleaseHugging Face has officially released version 1.0.0 of its core open-source library, Accelerate. This is a milestone update, signifying that since the project's…
從 DeepSpeed 到 FSDP 再切換回來：使用 Hugging Face Accelerate 實現無縫分散式訓練★ 75
Hugging Face Blog731 days agoTutorialIn the era of large language models (LLMs), the VRAM of a single GPU is often insufficient to hold models with tens of billions of parameters. To overcome this…
使用 DeepSpeed 與 Accelerate 實現極速 BLOOM 模型推理
Hugging Face Blog1,367 days agoTutorialBLOOM is a massive open-source multilingual model with 176 billion parameters. Running BLOOM at FP16 precision requires at least 352 GB of video memory (VRAM)…
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 Blog1,972 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…
使用區塊稀疏矩陣（Block Sparse Matrices）打造更小、更快的語言模型
Hugging Face Blog2,103 days agoTutorialIn the field of natural language processing (NLP), the Transformer architecture has become the dominant paradigm, but its core self-attention mechanism…