# lakshayg/tensorflow-build-archived

TensorFlow binaries supporting AVX, FMA, SSE

Repository: https://github.com/lakshayg/tensorflow-build-archived
Canonical: https://ross.abutalabs.com/products/tensorflow-build-archived
Language: Shell
License Family: other
Topics: machine-learning, tensorflow, simd-instructions
Archived: true
Last push: 2020-02-04T08:22:57+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3395, "days_push": 2402, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1891, forks 218 (observed 2026-08-28T04:05:49.630861+00:00)

## What it is
An archived repository of prebuilt TensorFlow binary wheels compiled with SIMD instruction sets (AVX, FMA, SSE) for CPUs lacking official wheel support. It has moved to lakshayg/tensorflow-build and has not been updated since 2020.

## Use cases
- install tensorflow on a cpu without avx support
- download prebuilt tensorflow wheels with fma enabled
- run tensorflow on older hardware without building from source
- find tensorflow binaries optimized for simd instructions

## When to choose
- you need a legacy TensorFlow build for old CPUs on an unsupported platform
- you want to avoid compiling TensorFlow from source for an older machine

## When to avoid
- you need current TensorFlow versions or security updates
- your CPU supports the official wheels
- you require an actively maintained project with a license

## Facets
- artifact type: dataset
- maturity: abandoned
- function: machine-learning, llm-training
- domain: machine-learning, deep-learning, developer-tools
- platform: python
- tags: tensorflow, prebuilt-binaries, simd, avx, fma, sse, pip-wheels, archived, linux, macos

## Member repositories
- lakshayg/tensorflow-build-archived (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:49.630861+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:13:00.518413+00:00, confidence not recorded.
  - readme: https://github.com/lakshayg/tensorflow-build-archived (fetched 2026-08-28T04:05:49.630861+00:00, sha 68c6940c840e)
- Data as of 2026-08-30T08:39:29.467469+00:00.