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Welcome to H2O LLM Studio, a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). You can also use H2O LLM Studio with the command line interface (CLI) and specify the configuration file that contains all the experiment parameters. To finetune using H2O LLM Studio with CLI, activate the pipenv environment by running make shell. With H2O LLM Studio, training your large language model is easy and intuitive. First, upload your dataset and then start...
A platform for rapid Reinforcement Learning methods development
Application allowing convenient experimentation in Reinforcement Learning - a Machine Learning domain. Project goals are:
- keep adding new environments and agents as simple as possible
- provide a rich set of state-of-art algorithms and problems
- integrate with other existing Reinforcement Learning platforms
If you found this application useful please cite this work: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6643987
RL Poker is a study project Java implementation of an e-soft on-policy Monte Carlo Texas Hold'em poker reinforcement learning algoritm with a feedforward neural network and backpropagation. It provides a graphicalinterface to monitor game rounds.
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