1 citations · 2 across the 14 of their papers we have counts for
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Sketch: A Toolkit for Streamlining LLM Operations
Xin Jiang, Xiang Li, Wenjia Ma +8
Large language models (LLMs) represented by GPT family have achieved remarkable success. The characteristics of LLMs lie in their ability to accommodate a wide range of tasks throu…
Open-domain Implicit Format Control for Large Language Model Generation
Yiqun Yao, Wenjia Ma, Xuezhi Fang +7
Controlling the format of outputs generated by large language models (LLMs) is a critical functionality in various applications. Current methods typically employ constrained decodi…
52B to 1T: Lessons Learned via Tele-FLM Series
Xiang Li, Yiqun Yao, Xin Jiang +17
Large Language Models (LLMs) represent a significant stride toward Artificial General Intelligence. As scaling laws underscore the potential of increasing model sizes, the academic…
Tele-FLM Technical Report
Xiang Li, Yiqun Yao, Xin Jiang +17
Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications. However, there is a notable p…
Not All Layers of LLMs Are Necessary During Inference
Siqi Fan, Xin Jiang, Xiang Li +6
Due to the large number of parameters, the inference phase of Large Language Models (LLMs) is resource-intensive. However, not all requests posed to LLMs are equally difficult to h…