tf-keras
Deep learning for humans.
Decision gist · record as of 2026-08-14
Yes, if you are committed to TensorFlow-based deep learning. TF-Keras is production-stable, actively maintained, has low install friction, and carries a permissive Apache 2.0 license. No known vulnerabilities. Install it as the standard Keras API for TensorFlow projects; consider Keras 3 only if you need multi-backend flexibility.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later and TensorFlow as a runtime dependency.
- Low install friction with a pure Python wheel.
- Actively maintained with a recent commit on 2026-08-14 and production-stable status.
License · maintenance · safety
Apache 2.0 (permissive) — Licensed under Apache 2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions.
last release 2026-03-18 (149 days) · last repo commit 2026-08-14 · 90 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 3,930,621 downloads/mo, #2,447 on PyPI
Alternatives
Verify before relying
pip install tf-keras
import tensorflow as tf
from tensorflow import keras
model = keras.Sequential([keras.layers.Dense(10, activation='relu')])
model.compile(optimizer='adam', loss='mse')- Whether TF-Keras 2.21.0 is compatible with all current TensorFlow versions or has specific version constraints.
- Performance characteristics compared to the multi-backend Keras 3 implementation.
What it is and what it does
TF-Keras is the TensorFlow-native implementation of Keras, descended from the legacy `tf.keras` codebase. It provides a high-level, user-friendly API for defining, training, and evaluating deep neural networks using TensorFlow as the computational backend. The package includes layers, optimizers, loss functions, and utilities for building models ranging from simple sequential architectures to complex custom networks.
Unlike the newer Keras 3 (multi-backend implementation supporting JAX, PyTorch, and TensorFlow), TF-Keras is specifically optimized for TensorFlow workflows. It is production-stable and actively maintained, making it suitable for projects where TensorFlow is the primary or exclusive deep learning framework.
Use it for
- Build and train sequential or functional neural network models for image classification, NLP, or regression tasks.
- Rapidly prototype deep learning models using high-level Keras layers and pre-built components.
- Fine-tune pre-trained models or transfer learning workflows within a TensorFlow ecosystem.
- Define custom layers and loss functions for specialized deep learning research or production systems.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are committed to TensorFlow-based deep learning.
TF-Keras is production-stable, actively maintained, has low install friction, and carries a permissive Apache 2.0 license. No known vulnerabilities. Install it as the standard Keras API for TensorFlow projects; consider Keras 3 only if you need multi-backend flexibility.
Install
tf-keras on PyPI
Before you install
Low install friction with a pure Python wheel. Actively maintained with a recent commit on 2026-08-14 and production-stable status. Requires Python 3.10 or later.
Requires Python 3.10 or later and TensorFlow as a runtime dependency.
License in practice
Licensed under Apache 2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions.
Quickstart
pip install tf-keras
import tensorflow as tf
from tensorflow import keras
model = keras.Sequential([keras.layers.Dense(10, activation='relu')])
model.compile(optimizer='adam', loss='mse')Verify before relying
- Whether TF-Keras 2.21.0 is compatible with all current TensorFlow versions or has specific version constraints.
- Performance characteristics compared to the multi-backend Keras 3 implementation.
Package facts
| License | Apache 2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagetensorflow |
| Maintenance | Actively maintained 149 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 3,930,621 / month, #2,447 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: MathematicsTopic :: Software DevelopmentTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python Modules |
Evidence: tf_keras-2.21.0-py3-none-any.whl
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See also Keras-Preprocessing · tf-keras-nightly · tensorflow-addons · keras · keras-nightly · keras-nlp · keras-hub · tf-slim · tensorflow · efficientnet