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The docs say "As long as a DB supports filtering and 3 main query types: raw samples, group by string and group by integer, snorkel can run queries against it (snorkel just needs to be shown how)."
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* https://github.com/snorkel-team/snorkel-extraction/tree/master/tutorials/workshop
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In my problem output is an integer number. I have some rules by which I can say about the possible range in which that number will be. So for some input if actual output is 1000. I have some rules …
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Please see the attached screenshots.
The string I'm searching is "uńicode".
The error message is: "'ascii' codec can't encode character u'\u0144' in position 1: ordinal not in range(128)".
![…
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## Proposer
ODI
## Use Case
As a participant in a sporting activity, I want to know what formal qualifications (e.g., swimming certificate, archery training, health commitment statement) I ne…
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In Palo Alto.
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I'd like to utilise these labels for another project. It seems the folder
```
snorkeling/disease_gene/disease_associates_gene/data/sentences
```
should also have `snorkel_labels_train.xlsx` to go …
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I review the code located in train_sts_qqp_crossdomain.py
The idea is to use cross_encoder's higher performance.
So for unlabeled data, is it feasible to combine multi sample methods with cross_encode…
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I downloaded the repo and then tried to run it in a Jupyter notebook but got the following error:
```
---------------------------------------------------------------------------
NameError …
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## Is your feature request related to a problem? Please describe.
I love `snorkel.labeling.filter_unlabeled_dataframe()`. I want a pyspark equivalent: `snorkel.labeling.filter_unlabeled_spark_rdd` …