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d4l3k/tfquantize

Analysis updated 2026-07-18 · repo last pushed 2018-06-18

Audience · developerComplexity · 3/5DormantSetup · moderate

TLDR

A Go library that shrinks trained TensorFlow models by reducing number precision, so they load faster and run quicker in production.

Mindmap

mindmap
  root((repo))
    What it does
      Quantizes TensorFlow models
      Reduces number precision
      Shrinks model size
    Tech stack
      Go
      TensorFlow
    Use cases
      Faster inference
      Smaller deployments
      Backend ML services
    Audience
      Go developers
      ML engineers
    Tradeoffs
      Slight accuracy drop
      Faster CPU loading
      Bridges Python to Go

Code map

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What do people build with it?

USE CASE 1

Compress a Python-trained TensorFlow model for deployment in a Go backend service.

USE CASE 2

Reduce model size and memory use for a mobile or embedded system with limited resources.

USE CASE 3

Speed up a backend service that scores thousands of prediction requests per second.

What is it built with?

GoTensorFlow

How does it compare?

d4l3k/tfquantize00kaku/gallery-slider-block04amanrajj/netwatch
Stars——0
Language—JavaScriptRust
Last pushed2018-06-182021-05-19—
MaintenanceDormantDormant—
Setup difficultymoderateeasymoderate
Complexity3/52/53/5
Audiencedevelopergeneralops devops

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 1h+

Requires a pre-trained TensorFlow model and Go's TensorFlow bindings set up first.

No license information was found in the explanation.

Copy-paste prompts

Prompt 1
Show me how to use tfquantize to compress a TensorFlow model I trained in Python for use in Go.
Prompt 2
Explain the tradeoff between model accuracy and speed when using this quantization library.
Prompt 3
Walk me through deploying a quantized TensorFlow model in a Go backend service.
Prompt 4
Help me understand how reducing number precision shrinks a machine learning model's size.

Frequently asked questions

What is tfquantize?

A Go library that shrinks trained TensorFlow models by reducing number precision, so they load faster and run quicker in production.

Is tfquantize actively maintained?

Dormant — no commits in 2+ years (last push 2018-06-18).

What license does tfquantize use?

No license information was found in the explanation.

How hard is tfquantize to set up?

Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.

Who is tfquantize for?

Mainly developer.

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