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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?
Fitting model: XGBoost ...
-34.1179 = Validation root_mean_squared_error score
10.58s = Training runtime
0.03s = Validation runtime
Fitting model: NeuralNetMXNet ...
-34.2849 = Validation root_mean_squared_error score
43.63s =
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[Error Message] Improve error message in SentencepieceTokenizer when arguments are not expected.
Description
While using tokenizers.create with the model and vocab file for a custom corpus, the code throws an error and is not able to generate the BERT vocab file
Error Message
ValueError: Mismatch vocabulary! All special tokens specified must be control tokens in the sentencepiece vocabulary.
To Reproduce
from gluonnlp.data import tokenizers
tokenizers.create('spm', model_p
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The generator currently outputs TypeScript projects only. It should have an option to output JavaScript projects.
This could be accomplished without duplicating code by the following steps
- If the TypeScript option is selected, continue as normal
- If the JavaScript option is selected, run all the same steps as the TypeScript generator, but add the following steps afterwards:
- Run
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There are many links in Kinetics that have expired. As as result, everyone might not be using the same Kinetics dataset. As a reference, the statistics of the Kinetics dataset used in PySlowFast can be found here, https://github.com/facebookresearch/video-nonlocal-net/blob/master/DATASET.md. However, I cannot seem to find similar information for gluoncv. Will you guys be sharing the statistics and