Daniel Whitenack
Daniel Whitenack
https://twitter.com/golang_news/status/918977049875877889
We should have a hosted Go notebook(s) with tutorials, information, etc. Contributors should be able to add to the content.
Add LLM wrapper and examples for [Prediction Guard](https://beta.predictionguard.com/). The Prediction Guard docs can be found [here](https://docs.predictionguard.com/). If you aren't familiar with this project: > With Prediction Guard you: > -...
# Update Prediction Guard LLM wrapper to the latest version/ functionality No dependencies updates here, but updating the LLM wrapper for [Prediction Guard](https://www.predictionguard.com/) to the latest version of the Python...
Following the `classification_sample`, implement a way to return the top N results from an inference along with the probabilities.
Implement an inference in as much as what is done in the `classification_sample`.
Wrap the image loading functionality of the inference engine, mirroring what happens in the `classification_sample`.
Figure out how to replicate the Inference Engine Configurator functionality in the `classification_sample` to initialize the inference engine.
As discussed in our recent meeting, https://github.com/kubeflow/kubeflow/issues/151#issuecomment-371628634 requires a way to expose data from Pachyderm to a TFJob. Moreover, this type of data access pattern would be useful for integrating...