BitNet b1.58 2B4T Technical Report
원문 초록
We introduce BitNet b1.58 2B4T, the first open-source, native 1-bit Large Language Model (LLM) at the 2-billion parameter scale. Trained on a corpus of 4 trillion tokens, the model has been rigorously evaluated across benchmarks covering language understanding, mathematical reasoning, coding proficiency, and conversational ability. Our results demonstrate that BitNet b1.58 2B4T achieves performance on par with leading open-weight, full-precision LLMs of similar size, while offering significant advantages in computational efficiency, including substantially reduced memory footprint, energy consumption, and decoding latency. To facilitate further research and adoption, the model weights are released via Hugging Face along with open-source inference implementations for both GPU and CPU architectures.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation
Speeding up Local Optimization in Vehicle Routing with Tensor-based GPU Acceleration
Specification-based Security Evaluation of Real-World Agents Tool-Calling under Long-Horizon Context Tasks
Making Language Model a Hierarchical Classifier and Generator
InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofing
Describe Anything Model for Visual Question Answering on Text-rich Images
토론
이 논문과 연결된 포럼 글이 아직 없습니다.