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transfer-learning
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Many users in our community have been asking to have easier ways to return the output of intermediate nodes. I can see that this could be very useful for debugging and also qualitative evaluation.
I think this feature would be very useful, though the exact design is not yet fully clear.
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I'm playing around with this wonderful code but I'm running into a curious issue when I try to train the model with my own data.
I replicated the personachat_self_original.json
file structure and added my own data. I deleted dataset_cache_OpenAIGPTTokenizer
file but when I try to train, I get this error:
INFO:train.py:Pad inputs and convert to Tensor
Traceback (most recent call last)
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when printing these objects we do not see informative content.
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Per this comment in #12
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We have a lot of antiquated docstrings that don't render well into ReadTheDocs. A kind of grunge (but incredibly useful) task would be to refactor these docstrings into proper ReadTheDocs format. This would allow us to render them effectively...
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When running TabularPredictor.fit(), I encounter a BrokenPipeError for some reason.
What is causing this?
Could it be due to OOM error?