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Hello, congratulations on your work. How could someone reproduce the STS experiments?

Preprocess not working

2

Hello, I am trying to run preprocess on provided [Wiki10-31K](https://drive.google.com/open?id=1Tv4MHQzDWTUC9hRFihRhG8_jt1h0VhnR) dataset. However, I am facing the following error: ```python Traceback (most recent call last): File "/content/AttentionXML/preprocess.py", line 17, in from...

Walking Syntax Trees

4

I am currently using the following method to walk the tree: ```python def traverse(tree): def _traverse(node): print_node(node) for child in node.children: _traverse(child) _traverse(tree.root_node) ``` How could someone do the same...

Call a REST API secured by keycloak from a desktop app

2

Hello, Thanks a lot for the great tutorial on keycloak. Could you help me a little more? I have a REST API implemented in Spring Boot and a Desktop app...

Timeout when trying to process nearby search request

3

I'm facing a timeout when trying to process the following request: ```python gmaps = googlemaps.Client(key="my_api_key") result = gmaps.places_nearby(location="-23.5506507,-46.6333824", type="store", radius=1000) ``` The complete error stack tracing is: ```python --------------------------------------------------------------------------- Timeout...

Hello, My fitness implementation, looks like: fitness = surprise + efficiency Efficiency is a value in an interval between 0 and 1. However, the surprise value can assume any value...

How to get the predicted labels as plain text?

1

Hello, After the prediction step in the [XR-Transformer tutorial](https://github.com/amzn/pecos/tree/mainline/pecos/xmc/xtransformer#python-example), how to get the predicted labels as plain text? Thank you.

XR-Transformer prediction step

2

After training the XTransformer model, I have been trying to generate the predictions as follows: ```python test_texts, test_texts_rpr = ... # test_texts: list of 34681 texts # test_text_rpr: csr_matrix of...

Could you link the data (`MSMARCO/triples.train.small.tsv`", `MSMARCO/queries.train.small.tsv`, `MSMARCO/collection.tsv`) used on the training script below: ```python from colbert.infra import Run, RunConfig, ColBERTConfig from colbert import Trainer if __name__=='__main__': with Run().context(RunConfig(nranks=4, experiment="msmarco")):...

Is there an approach that allows integration between omegaconf and [AWS Sagemaker Estimator's](https://sagemaker.readthedocs.io/en/stable/api/training/estimators.html) hyperparameters.