The organization tatsu-lab hosts a diverse array of public repositories on GitHub, primarily utilizing Python and Jupyter Notebook. Notable projects include stanford_alpaca, a framework for training language models, and alpaca_eval, an automatic evaluator for instruction-following models, showcasing their focus on machine learning and artificial intelligence.
Code and documentation to train Stanford's Alpaca models, and generate the data.
An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.
A simulation framework for RLHF and alternatives. Develop your RLHF method without collecting human data.
GPT4 based personalized ArXiv paper assistant bot
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Align your LM to express calibrated verbal statements of confidence in its long-form generations.
Code Release for "On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies"
Fast ImageNet training code with FFCV
Tatsu-lab builds various projects on GitHub, focusing on machine learning and artificial intelligence. Their notable repositories include stanford_alpaca for language model training and alpaca_eval for evaluating instruction-following models.
Tatsu-lab primarily uses Python and Jupyter Notebook in its public repositories. These languages are well-suited for their work in machine learning and data analysis.
Yes, all of tatsu-lab's repositories are public. This openness allows collaboration and contribution from the community, fostering innovation in their projects.
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