Example 1:

Example 2:

(Normal title format example)

(Example of converting the title into the LLM large model Jason format)
 

The latest version of LLM large model training data package in 2025 (U.S. teaching category ) This data is collected from U.S. teaching companies, teaching platforms, U.S. learning institutions, U.S. university teaching materials, etc. Chegg data contains 15%.

The data includes the question-answer format of the original data and the standard format that has been converted into suitable for large model training.

The LLM large model training data package (U.S. teaching type) includes:

• Teaching questions and answers from over 500 teaching companies, platforms, schools, and institutions around the world
• Original data (questions, answers, student texts, tutor teaching materials, auxiliary teaching materials, etc.), trained data (Jason data), data usage guide
  
  LLM large model training data package (U.S. teaching type ) usage process

1. Purchase & Download

   • Choose to purchase the LLM large model training data package (US teaching category ) on the platform .
   • Once payment is completed, you will be notified of the download link or data delivery method.
   • Download the data package to the local storage device.

2. Unzip and organize

   • Once the download is complete, extract the data package, which is usually compressed in ZIP or RAR format.
   • Data files will be classified and organized according to language, academic level (such as high school, university) and specific fields (such as Chinese, mathematics, statistics, etc.) for easy search and use .

3. Data preprocessing

   • The data has been formatted to adapt to standard AI model training frameworks (such as PyTorch, TensorFlow, etc.).
   • Check for noise or non-compliant content in the data to ensure the accuracy of training.

4. Import model training environment

   • Import data into your model training environment .
   • Make sure the data loading meets the input requirements of the model, such as input data format, batch size, etc.

5. Model Training

   • 95% of this data package is mainly in English, with about 5% in other languages.
   • Combined with the teaching knowledge in the data, the model can be applied to multiple fields such as natural language processing, intelligent answering , problem-solving systems, teaching planning, etc.

6. With this data package, you will easily obtain high-quality teaching data of various categories and academic levels to empower your AI model.

7. Optimization and debugging

   • During the training process, adjust the model parameters, optimizer, learning rate, etc. according to the preliminary results to improve the accuracy and performance of the model.
   • Compare the impact of data from different academic fields on the model results to ensure comprehensive coverage of required knowledge points.

8. Output and Application

   • After training, the model will be used in application scenarios such as teaching, educational platforms, etc.
   • The multi-language and multi-level data in the data package supports a wide range of application scenarios, especially AI projects involving the global teaching field.
     
     Release date: February 19, 2025 (This data package will update and increase the data volume every 3 months. Users who have purchased it can get the latest data for free in the download link)
     Update log: On March 31, 2025, the second data package was released, containing more than 100 million data items, with 0% duplication with the first data package.
     Update log: On April 1, 2025, the third data package was released, containing more than 100 million data items, with 0% duplication rate with the first and second data packages.