Pythia vs Streamlit
Overview
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Detailed Comparison
A modular framework for supercharging vision and language research built on top of PyTorch. | It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API. |
Model Zoo;
Multi-Tasking;
Datasets: Includes support for various datasets built-in including VQA, VizWiz, TextVQA and VisualDialog;
Modules: Provides implementations for many commonly used layers in vision and language domain;
Distributed: Support for distributed training based on DataParallel as well as DistributedDataParallel;
Unopinionated: Unopinionated about the dataset and model implementations built on top of it;
Customization: Custom losses, metrics, scheduling, optimizers, tensorboard; suits all your custom needs | Free and open source; Build apps in a dozen lines of Python with a simple API; No callbacks; No hidden state; Works with TensorFlow, Keras, PyTorch, Pandas, Numpy, Matplotlib, Seaborn, Altair, Plotly, Bokeh, Vega-Lite, and more
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Statistics | |
GitHub Stars - | GitHub Stars 42.1K |
GitHub Forks - | GitHub Forks 3.9K |
Stacks 0 | Stacks 403 |
Followers 8 | Followers 407 |
Votes 0 | Votes 12 |
Pros & Cons | |
No community feedback yet | Pros
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Integrations | |
What are some alternatives to Pythia, Streamlit?
TensorFlow
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scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
PyTorch
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Keras
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Kubeflow
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TensorFlow.js
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MLflow
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H2O
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PredictionIO
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