This project is temporarily on hold.\ I am now working on Ava, Personal Language Server, a GUI app for running LLMs.
JavaScript bindings for the GGML library, a fast and lightweight tensor/machine-learning library implemented in C.
https://user-images.githubusercontent.com/3526922/236536800-fca4d729-3479-471a-aea5-2d0ae5df3fdf.mov
You can install ggml-js via npm:
npm install ggml-js
Here's an example of how to use ggml-js in your JavaScript code:
import { Context, F } from 'ggml-js/core'
// Create context, two 1D tensors and multiply them
const ctx = Context.init()
const a = ctx.newTensor1D('f32', 1)
const b = ctx.newTensor1D('f32', 1)
const ab = F.mul(a, b)
// Build the computation graph
const graph = ctx.buildForward(ab)
// Set values & compute the graph
a.set(0, 1.5)
b.set(0, 2)
graph.compute()
// Get result
console.log(ab.get(0))
ggml-js also provides modules for working with pre-trained models and tokenizers. Here's an example of how to use the RWKV model and BPETokenizer:
import { RWKV } from 'ggml-js/llms'
import { BPETokenizer } from 'ggml-js/tokenizers'
// see examples/rwkv.js for full example
const model = RWKV.loadFromFile(...)
const tokenizer = BPETokenizer.loadFromFile(...)
for (const t of model.generate(tokenizer.encode('Hello world!'))) {
process.stdout.write(tokenizer.decodeOne(t))
}
If you want to build ggml-js from source, you can clone the repository and run the following commands:
zig build
This project is licensed under the MIT License.
This project bundles GGML library by Georgi Gerganov, which is also licensed under the MIT License.