cerebros-core-algorithm-alpha
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david-thrower
The Cerebros package is an ultra-precise Neural Architecture Search (NAS) / AutoML that is intended to much more closely mimic biological neurons than conventional neural network architecture strategi...
# from #254 : A CICD scale copy of the HPO script for further study.
# Tweaks and refactors to ## **From #253** ## TO DO: - [x] ### Add to text generation samples: - temperature=0.75, top_k=75, top_p=0.98, presence_penalty=1.4, frequency_penalty = 1.4 - temperature=0.7, top_k=75,...
# Run an HPO study training NotGPT on the 681 sample World English Bible Genesis 40 token context length data set. ## From #252
# Test that this will run at the small scale to lint the larger scale container. ```Dockerfile FROM tensorflow/tensorflow:2.19.0 RUN apt update -y RUN apt upgrade -y RUN apt install...
# Reproduce #243 with penalties and perhaps a more tuned hyperparam range considering the results of the last run. ## From #240 (latest updates to API including penalties for repetition)
# On the Generative model proof of concept: Add system telemetry using MlFlow system metrics. - I want to collect metrics on the CPU / GPU and RAM pressure, etc....
Make an alternate API that mimics CerebrosSimpleRandomSearch but uses Optuna TPEsampler(multivariate=True) instead of random selections.
# Dev branch - Create a working branch to hold this vanilla scale NLP generative proof of concept that may be used in the future for CICD testing, while its...
From #230 Test out a simulated Voxel layer as an output.
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The Cerebros package is an ultra-precise Neural Architecture Search (NAS) / AutoML that is intended to much more closely mimic biological neurons than conventional neural network architecture strategi...