This is a directory that collects GLM's implementation over various NLP datasets. We feel lucky to collaborate with all contributors that share their implementations here.

If you also want to become a contributor of GLM, we encourage you to make PR to this repo according to the following PR rules. The maintainer will check the validity before accept the PR.

Each PR should include the code and markdown description in a subdirectory of the current examples directory. An example subdirectory tree is as follows:

└── examples
    └── <Your PR directory>: Huggingface Datasets identifier (recommended) or customized name
        ├── README.md
        ├── requirements.txt
        └── <Your code>

Please exclude data files in the PR as they take up too much space, and describe the method to acquire the data in your README.md.

Please at least include the following sections in your README to help its better use:

• Dataset Name: serves as the markdown title.
• Authors: Your name(s), contacts (email), and the url to your homepage(s) (if available).
• Task Description: A short paragraph to briefly introduce what the dataset and corresponding task is about.
• Running Commands: Provide the bash/shell commands for preprocessing, training, and inference.
• Results: Please provide your implementation's final performance, along with other available comparison methods'. Ensure that they are reproducible once using your provided Running Commands.
• Reference: Proper citation information for the dataset and related comparison methods.

Please include the necessary python packages in the file for other users to reproduce your results.

TODO