keras-core
keras-nlp
| keras-core | keras-nlp | |
|---|---|---|
| 1 | 2 | |
| 1,264 | 701 | |
| 0.0% | 3.1% | |
| 9.8 | 9.5 | |
| 7 months ago | 3 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
keras-core
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Keras Core: Keras for TensorFlow, Jax, and PyTorch
We are still working on this feature. We try to have it in model.compile(jit_compile=True). https://github.com/keras-team/keras-core/blob/v0.1.0/keras_c...
keras-nlp
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Keras 3.0
Yes, Keras can be used to build LLMs. In fact this is one of the main use cases.
There are some tutorials about how to do it "from scratch", like this: https://keras.io/examples/nlp/neural_machine_translation_wit...
Otherwise, if you want to reuse an existing LLM (or just see how a large one would be implemented in practice) you can check out the models from KerasNLP. For instance, this is BERT, basically just a stack of TransformerEncoders. https://github.com/keras-team/keras-nlp/blob/master/keras_nl...
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Keras Core: Keras for TensorFlow, Jax, and PyTorch
Yes, you can check out KerasCV and KerasNLP which host pretrained models like ResNet, BERT, and many more. They run on all backends as of the latest releases (today), and converting them to be backend-agnostic was pretty smooth! It took a couple of weeks to convert the whole packages.
https://github.com/keras-team/keras-nlp/tree/master/keras_nl...
What are some alternatives?
keras-cv - Industry-strength Computer Vision workflows with Keras
MAGIST-Algorithm - Multi-Agent Generally Intelligent Simultaneous Training Algorithm for Project Zeta
i6_experiments
returnn - The RWTH extensible training framework for universal recurrent neural networks
Spectrum - Spectrum is an AI that uses machine learning to generate Rap song lyrics
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.