wasi-nn VS ollama

I really like the post that they mention (https://www.secondstate.io/articles/fast-llm-inference/). The reasons for avoiding python all resonate with me. I'm excited to play with WASI-NN (https://github.com/WebAssembly/wasi-nn) and that rust code is very readable to load up a GGUL model.

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.

in machine learning (https://github.com/WebAssembly/wasi-nn)

Jan goes a step further by integrating with other local engines like LM Studio and ollama.

# install the Ollama curl -fsSL https://ollama.com/install.sh | sh # get the llama3 model ollama pull llama2 # install the MLFlow pip install mlflow

Ollama for running LLMs locally

curl -fsSL https://ollama.com/install.sh | sh

Streaming is not a problem (it's just a simple flag: https://github.com/wiktor-k/llama-chat/blob/main/index.ts#L2...) but I've never used voice input.

The examples show image input though: https://github.com/ollama/ollama/blob/main/docs/api.md#reque...

Maybe you can file an issue here: https://github.com/ollama/ollama/issues

I’m a huge fan of open source models, especially the newly release Llama 3. Because of the performance of both the large 70B Llama 3 model as well as the smaller and self-host-able 8B Llama 3, I’ve actually cancelled my ChatGPT subscription in favor of Open WebUI, a self-hostable ChatGPT-like UI that allows you to use Ollama and other AI providers while keeping your chat history, prompts, and other data locally on any computer you control.

Ollama for running LLMs locally

There are various other interesting options to set, but for those, I will direct you to the link to the documentation. During the OS Day, I had the chance to experiment a bit with the models offered by Ollama; in fact, if you need some inspiration, I invite you to check out the YouTube channel of Shroedinger Hat where you can find the videos of the individual talks, also organized in a single playlist; you will find more than one showing the use of Ollama for various projects and in various ways 😁