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祝贺!OpenBMB 核心成员入选 CCF 优博激励计划
1 月 4 日,中国计算机学会(CCF)公布了2022年“CCF优秀博士学位论文激励计划”入选名单,OpenBMB 核心成员韩旭的博士论文《开放域文本的结构化知识获取》入选。 2022年“CCF优秀
2023-01-19
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登顶 ZeroCLUE!CPM-Bee 凭什么这样强?
2022年10月13日,我们开启了CPM-Live第二期模型CPM-Bee的训练。在CPM-Ant的基础上,CPM-Bee考虑了任务模式增强、多语言融合、复杂结构处理等新特性。CPM-Bee训练即将完
2023-01-17
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小工具撬动大模型,『模力表格』惊喜问世
" CPM-Live CPM-Live CPM-Live 模力表格惊喜问世 🔔铛铛铛! CPM-Bee 训练即将圆满收官! 「模力表格」问世啦! 模力表格 是一款 大模型驱动的表格效
2023-01-13
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BM Architecture Diagram
BM Data BM Data BM Train Open Prompt Delta Center Open Delta BM Train Open Prompt BM Inf BM Inf BM Inf BM Cook BM Cook
BMTrain
The “engine” for big model training. BMTrain performs efficient pre-training and tuning for big models.
Compared with toolkit such as DeepSpeed, BMTrain can save 90% on cost in the training process.
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BMTrain performs amazingly compared to popular frameworks
BMCook
The toolkit for big model “slimming”. BMCook performs efficient compression for big models to improve operating efficiency.
Through the combination of algorithms such as quantization, pruning, distillation, and MoEfication, 90%+ effects of the original model can be maintained, and model inference can be accelerated by 10 times.
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Combination in Any Way
BMInf
Perform big model inference on a thousand-yuan GPU. BMInf performs low-cost and high-efficiency inference for big models,which can perform big model inference with more than 10 billion parameters on a single thousand-yuan GPU (GTX 1060).
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10B Model Decoding Speed
BMInf
PyTorch
OpenPrompt
A “sharp knife” for big model prompt learning. OpenPrompt provides a prompt learning template language with a unified interface. Its compositionality and modularity allow you to easily deploy prompt learning algorithms to run big models.
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Architecture
OpenDelta
Tiny parameters leverage big models. OpenDelta performs parameter-efficient tuning for big models. By only updating very few parameters (less than 5%), the algorithms can achieve the same effect with full-parameter fine-tuning.
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Tool Collaboration
ModelCenter
Big Model Warehouse.ModelCenter implements pre-trained language models (PLMs) based on BMTrain backend. It supports Efficient, Low-Resource, Extendable model usage and distributed training.
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Supported Models
Our Customers