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Project: edu-segmentation
Version: 0.0.115
Filename: edu_segmentation-0.0.115-py3-none-any.whl
Download: [link]
Size: 327174
MD5: 5e33cf11400aa2388296611fd2cce805
SHA256: 4d36694d8f38b62cbd80ae97067d281bfe7d1897fb702cf1dbd639e9dc2fd3a7
Uploaded: 2023-08-13 09:31:14 +0000

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METADATA · WHEEL · RECORD

METADATA

Metadata-Version: 2.1
Name: edu-segmentation
Version: 0.0.115
Summary: To improve EDU segmentation performance using Segbot. As Segbot has an encoder-decoder model architecture, we can replace bidirectional GRU encoder with generative pretraining models such as BART and T5. Evaluate the new model using the RST dataset by using few-shot based settings (e.g. 100 examples) to train the model, instead of using the full dataset.
Author: Your Name
Author-Email: you[at]example.com
Classifier: Programming Language :: Python :: 3
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Description-Content-Type: text/markdown
[Description omitted; length: 3152 characters]

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