Comments (2)
IanQS
commented on July 20, 2024
Isn't that literally one of the main points of ML? To make it generalize?
Also, "could apply" is pretty subjective
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ConnorJL
commented on July 20, 2024
The idea of unsupervised learning like this is that there is a lot of unstructured, useful information present in the wide range of text the model is trained on, and it is able therefor to learn useful things even without being given a specific goal. You can read some more about this in the original GPT2 paper.
Hope that helps!
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Related Issues (20)
- when reading metadata of gs://openwebtext/stuff/encoder/encoder.json HOT 1
- Your 1.5B model HOT 2
- error when using create_tfrecords.py HOT 3
- Are there some research papers about text-to-set generation? HOT 1
- How can i create smaller sized file for inference of 1.5B model HOT 1
- I figured out how to cram GPT-2 1.5B onto a single TPU core with Adam optimizer HOT 3
- Training on artificial language data (server logs, medical records, etc.) HOT 1
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- character-level HOT 1
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- Error on output HOT 1
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- where is the length of the forecast article set? Thank you!
- create_tfrecords.py。Dealing with problems with your own data set
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