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MedicalGPT download for Windows

Free download MedicalGPT Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named MedicalGPT whose latest release can be downloaded as v1.6.0sourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named MedicalGPT with OnWorks for free.

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- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

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MedicalGPT


DESCRIPTION

MedicalGPT training medical GPT model with ChatGPT training pipeline, implementation of Pretraining, Supervised Finetuning, Reward Modeling and Reinforcement Learning. MedicalGPT trains large medical models, including secondary pre-training, supervised fine-tuning, reward modeling, and reinforcement learning training.



Features

  • The first stage: PT (Continue PreTraining) incremental pre-training, pre-training the GPT model twice on massive domain document data to inject domain knowledge
  • The second stage: SFT (Supervised Fine-tuning) has supervised fine-tuning, constructs an instruction fine-tuning data set, and performs instruction fine-tuning on the basis of the pre-training model to align instruction intentions
  • The third stage: RM (Reward Model) reward model modeling, constructing a human preference ranking data set, training the reward model to align human preferences, mainly the "HHH" principle, specifically "helpful, honest, harmless"
  • The fourth stage: RL (Reinforcement Learning) is based on human feedback reinforcement learning (RLHF), using the reward model to train the SFT model, and the generation model uses rewards or penalties to update its strategy in order to generate higher quality, more in line with human preferences
  • We provide a simple Gradio-based interactive web interface
  • After the training is complete, now we load the trained model to verify the effect of the model generating text


Programming Language

Python


Categories

Large Language Models (LLM)

This is an application that can also be fetched from https://sourceforge.net/projects/medicalgpt.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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