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johndmulhausendependabot[bot]SinaMostafanejadgithub-actions[bot]
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Testing GPT Editor (CI version) (#1191)
Testing GPT Editor (CI version) --------- Signed-off-by: dependabot[bot] <[email protected]> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Sina Mostafanejad <[email protected]> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
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(?i)API
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(?i)app
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(?i)AutoTrain
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(?i)aws
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(?i)autogenerate
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(?i)chatbot
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(?i)automation
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(?i)autolog
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(?i)basename
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(?i)bokeh
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(?i)boolean
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(?i)checkpoint
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API
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[Aa]pps?
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AutoTrain
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AWS
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[Aa]utogenerates?
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[Aa]utomations?
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[Aa]utologs?
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[Bb]asenames?
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[Bb]okeh
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[Bb]oolean
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[Cc]hatbots?
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[Cc]heckpoints?
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(?i)cli
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(?i)cloud
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[Cc]loud
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(?i)cognito
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(?i)colab
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(?i)config
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[Cc]olab
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[Cc]onfig
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Databricks
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(?i)dataframe
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(?i)dataloader
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(?i)datastore
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(?i)dedicated cloud
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(?i)dequeue
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(?i)deserialize
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(?i)dequeues?
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(?i)deserializes?
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Docker
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Dockerfile
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Docsy
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(?i)downsample
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(?i)enqueue
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[Dd]ownsamples?
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[Ee]nqueues?
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Entra
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(?i)eval
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(?i)gcp
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[Ee]vals?
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GCP
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(?i)github
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GPU
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Gradio
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Helm
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(?i)hostname
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[Hh]ostnames?
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HTML
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Hyperband
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(?i)hyperparameter(s)
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[Hh]yperparameters?
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JWT
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Kaniko
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(?i)keras
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Keycloak
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(?i)keypoint
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[Kk]eypoints?
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Kubeflow
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Kubernetes
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kfp
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(?i)latent
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[Ll]atent
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LLMOps
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LLMs
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Matplotlib
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MMEngine
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MMDetection
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MLOps
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(?i)namespace
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[Nn]amespaces?
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OAuth
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Okta
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OpenID Connect
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(?i)operator
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[Oo]perators?
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Optuna
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Plotly
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(?i)prepend
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(?i)pseudocode
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PyTorch Profiler
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(?i)registry
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(?i)reinitialize
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[Rr]egistry
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[Rr]egistries
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[Rr]einitialize
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(?i)roc
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SCIM
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SageMaker
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(?i)scatterplot
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(?i)subcommand
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[Ss]catterplot
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[Ss]ubcommand
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[Ss]paCy
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(?i)self-managed
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[Ss]elf-managed
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TensorBoard
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TensorFlow
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Terraform
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(?i)tooltip
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[Tt]ooltips?
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TTL
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UI
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Ultra[Ll]ytics
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(?i)walkthrough
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[Ww]alkthroughs?
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wandb
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wandb.com
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W&B Models
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W&B Weave
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W&B Server
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(?i)webhook
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(?i)workspace
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[Ww]ebhooks?
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[Ww]orkspaces?
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content/_index.md

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##### Use AI models in your app
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Use [W&B Weave](https://weave-docs.wandb.ai/) to manage all aspects of integrating AI models into your code, including tracing, output evaluation, cost estimates, and using our LLM playground to help compare the various LLM models and their configuration paramaters.
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Use [W&B Weave](https://weave-docs.wandb.ai/) to manage AI models in your code. Features include tracing, output evaluation, cost estimates, and a playground for comparing different large language models (LLMs) and settings.
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- [Introduction](https://weave-docs.wandb.ai/)
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- [Quickstart](https://weave-docs.wandb.ai/quickstart)
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</div>
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<h2>W&B Models</h2>
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##### Build AI models
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##### Develop AI models
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Use [W&B Models]({{< relref "/guides/" >}}) to manage all aspects of building your own AI models, including training, fine-tuning, reporting, automating hyperparameter sweeps, and using our model registry to assist with versioning and reproducibility.
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Use [W&B Models]({{< relref "/guides/" >}}) to manage AI model development. Features include training, fine-tuning, reporting, automating hyperparameter sweeps, and utilizing the model registry for versioning and reproducibility.
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- [Introduction]({{< relref "/guides/" >}})
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- [Quickstart]({{< relref "/guides/quickstart/" >}})

scripts/check_header.py

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