WasmEdge-image
SSVM
| WasmEdge-image | SSVM | |
|---|---|---|
| 1 | 50 | |
| 5 | 7,952 | |
| - | 1.7% | |
| 3.5 | 9.7 | |
| 10 months ago | 3 days ago | |
| C | C++ | |
| - | Apache License 2.0 |
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.
WasmEdge-image
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Streaming Image Recognition by WebAssembly and Tensorflow
$ wget https://github.com/second-state/WasmEdge-image/releases/download/0.8.0/WasmEdge-image-0.8.0-manylinux2014_x86_64.tar.gz $ sudo tar -C /usr/local/ -xzf WasmEdge-image-0.8.0-manylinux2014_x86_64.tar.gz $ sudo ldconfig
SSVM
- A WASM runtime for running LLMs locally
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Time-series data ingestion from Rust WebAssembly application, leveraging GreptimeDB and WasmEdge
WasmEdge GitHub address: https://github.com/WasmEdge/WasmEdge.
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Orca-2-13B Runs Directly on Rust+WASM – No Python/C++ Hassles
I see that they recently changed the intro of WasmEdge on Github [1] to " WasmEdge is the easiest and fastest way to run LLMs on your own devices. "
Since it's a wasm runtime capable of many things I find bizarre that they now start describing it with a ultra-specific use case
- [1] https://github.com/WasmEdge/WasmEdge
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Run LLMs on my own Mac fast and efficient Only 2 MBs
Mmm…
The wasm-nn that this relies on (https://github.com/WebAssembly/wasi-nn) is a proposal that relies of arbitrary plugin backends sending arbitrarily chunks to some vendor implementation. The api is literally like set input, compute, set output.
…and that is totally non portable.
The reason this works, is because it’s relying on the abstraction already implemented in llama.cpp that allows it to take a gguf model and map it to multiple hardware targets,which you can see has been lifted here: https://github.com/WasmEdge/WasmEdge/tree/master/plugins/was...
So..
> Developers can refer to this project to write their machine learning application in a high-level language using the bindings, compile it to WebAssembly, and run it with a WebAssembly runtime that supports the wasi-nn proposal, such as WasmEdge.
Is total rubbish; no, you can’t.
This isn’t portable.
It’s not sandboxed.
If you have a wasm binary you might be able to run it if the version of the runtime you’re using happens to implement the specific ggml backend you need, which it probably doesn’t… because there’s literally no requirement for it to do so.
There’s a lot of “so portable” talk in this article which really seems misplaced.
- Security Slam 2023: Contribute to WasmEdge and Elevate Open Source Security
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Requiem for a Stringref
WasmEdge isn't there yet: https://github.com/WasmEdge/WasmEdge/issues/1122#issuecommen...
- Should You Be Scared of Unix Signals?
- WasmEdge 0.13.0: Unified CLI, ARM Support and Migrating Extensions to Plugins
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ChatGPT-powered code review bot to boost your PR merge. Deploy in 5 mins
Example 1: Analyze the content and risks of each commit in the PR. Then make a summary. https://github.com/WasmEdge/WasmEdge/pull/2394#issuecomment-...
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Cloud, Why So Difficult?
There has also been a few "cloud-native" runtimes based on WASM, like WasmEdge but there's a few others (can't remember their names!)...
What are some alternatives?
WasmEdge-tensorflow
wasmer - 🚀 The leading Wasm Runtime supporting WASIX, WASI and Emscripten