Juyongjiang John Github Phd candidate (sep. 2022 now) at hkust. working on ai coding, code rl & agent. looking for an internship. 🚀 juyongjiang. Juyongjiang.github.io | john john juyongjiang.github.io.
Juyongjiang John Github Juyongjiang codeup llama 2 13b chat hf text generation • updated oct 6, 2023• 24 • 32. Department of computer science, hong kong baptist university. proceedings of the 32nd acm international conference on information and … proceedings of the forty second international conference on. Phd candidate (sep. 2022 now) at hkust. working on llms, with a focus on code generation. 🚀 looking for collaborators and internships. 🤗 juyongjiang. Contribute to juyongjiang juyongjiang development by creating an account on github.
Github Juyongjiang Openglexperiment Computer Graphics Opengl Phd candidate (sep. 2022 now) at hkust. working on llms, with a focus on code generation. 🚀 looking for collaborators and internships. 🤗 juyongjiang. Contribute to juyongjiang juyongjiang development by creating an account on github. Github is where people build software. more than 150 million people use github to discover, fork, and contribute to over 420 million projects. Phd candidate (sep. 2022 now) at hkust. working on ai coding, code rl & agent. 🚀 juyongjiang. In this paper, we therefore address the long tailed problem from feature space and thereby propose the feature balanced loss. specifically, we encourage larger feature norms of tail classes by giving them relatively stronger stimuli. We propose the development of an instruction following multilingual code generation model based on llama x.
John0209 TuẠN Vå â Github Github is where people build software. more than 150 million people use github to discover, fork, and contribute to over 420 million projects. Phd candidate (sep. 2022 now) at hkust. working on ai coding, code rl & agent. 🚀 juyongjiang. In this paper, we therefore address the long tailed problem from feature space and thereby propose the feature balanced loss. specifically, we encourage larger feature norms of tail classes by giving them relatively stronger stimuli. We propose the development of an instruction following multilingual code generation model based on llama x.
John Agyemang Github In this paper, we therefore address the long tailed problem from feature space and thereby propose the feature balanced loss. specifically, we encourage larger feature norms of tail classes by giving them relatively stronger stimuli. We propose the development of an instruction following multilingual code generation model based on llama x.
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