lst-bench
netron
| lst-bench | netron | |
|---|---|---|
| 1 | 36 | |
| 55 | 26,256 | |
| - | - | |
| 8.8 | 9.9 | |
| 4 days ago | 7 days ago | |
| Java | JavaScript | |
| Apache License 2.0 | MIT License |
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.
lst-bench
netron
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Your 14-Day Free Trial Ain't Gonna Cut It
They're data-dependence graphs for a neural-network scheduling problem. Like this but way bigger to start with and then lowered to more detailed representations several times: https://netron.app/?url=https://github.com/onnx/models/raw/m... My home-grown layout engine can handle the 12k nodes for llama2 in its highest-level form in 20s or so, but its not the most featureful, and they only get bigger from there. So I always have an eye out for potential tools.
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What's the best PyTorch model visualization tool?
Netron seems to be the best that I've seen so far. https://github.com/lutzroeder/netron
- Visualizer for neural network, deep learning and machine learning models
- Netron: Visualizer for Machine Learning Models
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
In exploring open-source projects, I've come across several promising tools capable of managing deep-learning models for images. Significantly, tools such as NETRON provide visualization of neural networks, while SHAP can be used for evaluating the significance of outputs.
- Netron is a viewer for neural network, deep learning and machine learning models
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Operationalize TensorFlow Models With ML.NET
We need to find out the exact input and output tensor names. A tool like Netron makes this super easy. Open the original .tflite and/or the ONNX model in Netron and click the Model Properties button in the lower left corner.
- Netron: A viewer for neural network, deep learning and machine learning models
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Visualize PyTorch Models with NNViz
How is this different from e.g Netron https://github.com/lutzroeder/netron
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[P]Visualizing a neural network.
Netron (https://netron.app/) is the best and mostly used NN visualizer. Just save your model and then simply load it via netron to look its layers and weights. If you want a more complex visualization then you can also play with Zetane ( but its paid, also have a free version) engine.
What are some alternatives?
openvino_notebooks - 📚 Jupyter notebook tutorials for OpenVINO™
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
chat-ui - Open source codebase powering the HuggingChat app
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
FLiPStackWeekly - FLaNK AI Weekly covering Apache NiFi, Apache Flink, Apache Kafka, Apache Spark, Apache Iceberg, Apache Ozone, Apache Pulsar, and more...
models - Models and examples built with TensorFlow
starcoder - Home of StarCoder: fine-tuning & inference!
pwnagotchi - (⌐■_■) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning.
serving-pytorch-models - Serving PyTorch models with TorchServe :fire:
PlotNeuralNet - Latex code for making neural networks diagrams
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
onnx-tensorflow - Tensorflow Backend for ONNX