cape-js
onnxruntime
cape-js | onnxruntime | |
---|---|---|
4 | 54 | |
22 | 12,804 | |
- | 3.3% | |
2.9 | 10.0 | |
11 months ago | 3 days ago | |
TypeScript | C++ | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
cape-js
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Confidential Optical Character Recognition Service With Cape
Once you have your access token, you can invoke the OCR service. Here is a code snippet showing you how to do it with cape-js.
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Hide And Seek
A running example of this code can be seen here on github. This example is run using the Cape-JS and the function is deployed using Cape CLI.
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Secure Sentiment Analysis with Enclaves
Cape provides a command line interface (CLI) and also a Python and JavaScript software development kits (SDKs) called pycape and cape-js that allow developers to deploy their apps and allow users to interact with them in a secure manner.
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Using a Random Forest Model for Fraud Detection in Confidential Computing
In addition to the platform itself, Cape also provides a CLI that enables its users to easily encrypt their input data, and deploy and run serverless functions with easy commands: cape encrypt, cape deploy, and cape run. Additionally, Cape also provides two SDKs: pycape and cape-js, which allow for using cape within Python and JavaScript programs respectively.
onnxruntime
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Machine Learning with PHP
ONNX Runtime: ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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AI Inference now available in Supabase Edge Functions
Embedding generation uses the ONNX runtime under the hood. This is a cross-platform inferencing library that supports multiple execution providers from CPU to specialized GPUs.
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Deep Learning in JavaScript
tfjs is dead, looking at the commit history. The standard now is to convert PyTorch to onnx, then use onnxruntime (https://github.com/microsoft/onnxruntime/tree/main/js/web) to run the model on the browsdr.
- FLaNK Stack 05 Feb 2024
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Vcc – The Vulkan Clang Compiler
- slang[2] has the potential, but the meta programming part is not as strong as C++, existing libraries cannot be used.
The above conclusion is drawn from my work https://github.com/microsoft/onnxruntime/tree/dev/opencl, purely nightmare to work with thoes drivers and jit compilers. Hopefully Vcc can take compute shader more seriously.
[1]: https://www.circle-lang.org/
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Oracle-samples/sd4j: Stable Diffusion pipeline in Java using ONNX Runtime
I did. It depends what you want, for an overview of how ONNX Runtime works then Microsoft have a bunch of things on https://onnxruntime.ai, but the Java content is a bit lacking on there as I've not had time to write much. Eventually I'll probably write something similar to the C# SD tutorial they have on there but for the Java API.
For writing ONNX models from Java we added an ONNX export system to Tribuo in 2022 which can be used by anything on the JVM to export ONNX models in an easier way than writing a protobuf directly. Tribuo doesn't have full coverage of the ONNX spec, but we're happy to accept PRs to expand it, otherwise it'll fill out as we need it.
- Mamba-Chat: A Chat LLM based on State Space Models
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VectorDB: Vector Database Built by Kagi Search
What about models besides GPT? Most of the popular vector encoding models aren't using this architecture.
If you really didn't want PyTorch/Transformers, you could consider exporting your models to ONNX (https://github.com/microsoft/onnxruntime).
- ONNX runtime: Cross-platform accelerated machine learning
- Onnx Runtime: “Cross-Platform Accelerated Machine Learning”
What are some alternatives?
pycape - The Cape Privacy Python SDK
onnx - Open standard for machine learning interoperability
cli - Cape Privacy CLI
onnx-tensorrt - ONNX-TensorRT: TensorRT backend for ONNX
doctr - docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
onnx-simplifier - Simplify your onnx model
cape-dataframes - Privacy transformations on Spark and Pandas dataframes backed by a simple policy language.
ONNX-YOLOv7-Object-Detection - Python scripts performing object detection using the YOLOv7 model in ONNX.
hideandseek
onnx-tensorflow - Tensorflow Backend for ONNX
functions - Sample functions for Cape Privacy
MLflow - Open source platform for the machine learning lifecycle