phi3-Chinese

Committed to collecting and organizing the various training variants of the phi3 model from the open source community, as well as providing tutorials for training, inference, and deployment.

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phi3-Chinese is a public GitHub repository that focuses on collecting and organizing various training variants of the phi3 model from the open source community. It not only provides download links for different versions of the phi3 model but also includes relevant tutorials for training, inference, and deployment, aiming to help developers better understand and utilize the phi3 model.

Offer download links for different versions of the phi3 model
Include simple tutorials for training
inference
and deployment
Dedicated to improving the feasibility of deployment on mobile devices
Collect distinctive and interesting weight sets to enhance the diversity of models
Discuss the current issues of the model and potential improvement directions

Appropriate for developers and researchers who can use these resources for model research and development
Suited for students and educators interested in natural language processing and machine learning
Ideal for enterprises that need to deploy lightweight models on mobile devices

Developers can use the phi3 model to understand and generate Chinese text
Researchers can conduct research on algorithm optimization and performance enhancement based on the phi3 model
Enterprises can develop intelligent customer service systems for the Chinese market using the phi3 model

Step 1: Visit the GitHub repository page to learn the basic information about phi3-Chinese
Step 2: Choose a suitable version of the phi3 model for download according to your needs
Step 3: Read and follow the tutorials provided in the repository to train and deploy the model
Step 4: If you encounter any issues
you can check the Issues section of the repository or participate in discussions

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Bounce Rate

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phi3-Chinese

phi3-Chinese Visit Over Time

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Gemma-2-27b — A lightweight, advanced open-weights text generation model

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