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BharatSahAIyak / autotune

A comprehensive toolkit for seamless data generation and fine-tuning of NLP models, all conveniently packed into a single block.
MIT License
9 stars 5 forks source link

Model deployment imporvements #112

Closed sooraj1002 closed 4 months ago

sooraj1002 commented 4 months ago

Summary by CodeRabbit

coderabbitai[bot] commented 4 months ago

[!WARNING]

Review failed

The pull request is closed.

Walkthrough

The changes involve improving the codebase by reorganizing imports, adjusting logging levels, and refining workflow parameters for more specific configurations. These modifications primarily aim to enhance readability, maintainability, and debugging capabilities during the deployment process.

Changes

Files Change Summary
workflow/training/deploy.py Imports reordering, logging level adjustments from info to debug, and workflow parameter modifications for deployment.
workflow/training/utils.py Reorganization of import statements by combining multiple imports into single lines for readability and maintainability.

Poem

In the world of code, changes weave,
Debugging whispers, logs now breathe.
Imports danced, a readable tune,
Refinements hum beneath the moon.
🐇✨ CodeRabbit grins, hopping 'round,
In this realm, improvements found.

[!TIP]

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