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https://github.com/hellojwilde/energetic-ai
EnergeticAI is TensorFlow.js, optimized for serverless environments, with fast cold-start, small module size, and pre-trained models.
https://github.com/hellojwilde/energetic-ai
ai artificial-intelligence embeddings embeddings-trained machine-learning sentence-embeddings tensorflow tensorflowjs
Last synced: 2 months ago
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EnergeticAI is TensorFlow.js, optimized for serverless environments, with fast cold-start, small module size, and pre-trained models.
- Host: GitHub
- URL: https://github.com/hellojwilde/energetic-ai
- Owner: hellojwilde
- License: apache-2.0
- Created: 2023-05-16T02:06:17.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-11-20T00:21:59.000Z (about 1 year ago)
- Last Synced: 2024-11-08T07:37:56.962Z (3 months ago)
- Topics: ai, artificial-intelligence, embeddings, embeddings-trained, machine-learning, sentence-embeddings, tensorflow, tensorflowjs
- Language: TypeScript
- Homepage: https://energeticai.org
- Size: 35.8 MB
- Stars: 35
- Watchers: 5
- Forks: 0
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Run open-source AI in serverless functions, up to 67x faster. Compatible with Tensorflow.js.
# EnergeticAI
EnergeticAI is a distribution of TensorFlow.js optimized for serverless functions:
- **small module size** (~3 MB vs. 146 MB - 513 MB for stock TensorFlow.js)
- **fast cold-start inference** (~50 ms vs. 2000+ ms for stock TensorFlow.js)
- **incredible ease-of-use** (pre-trained models for common cases)
It's intended to be a condensed replacement for TensorFlow.js, so you can use it with much existing code and models.
## Install
EnergeticAI is available on NPM.
Install the **core package**, along with any **model libraries** you want to use (e.g. embeddings):
```bash
npm install @energetic-ai/core @energetic-ai/embeddings @energetic-ai/model-embeddings-en
```
You can see a full list of packages below.
## Usage
Here's an example of using the embeddings model:
```js
import { initModel, distance } from "@energetic-ai/embeddings";
import { modelSource } from "@energetic-ai/model-embeddings-en";
(async () => {
const model = await initModel(modelSource);
const embeddings = await model.embed(["hello", "world"]);
console.log(distance(embeddings[0], embeddings[1])));
})();
```
## Packages
This repository contains the following packages:
| Package | Description |
| ------------------------------------- | -------------------------------------------------------------------- |
| **@energetic-ai/core** | The core EnergeticAI library, comparable to `@tensorflow\tfjs-core`. |
| **@energetic-ai/classifiers** | Classifiers model library. |
| **@energetic-ai/embeddings** | Embeddings model library. |
| **@energetic-ai/model-embeddings-en** | English embeddings model weights. |
See the readmes in the [packages](packages) directory for more information.
## Examples
See the [examples](examples) directory for examples.
## Development
This repository uses [Lerna](https://lerna.js.org/) to manage packages, and [Vitest](https://vitest.dev/) to run tests.
## License
[Apache 2.0](LICENSE), except for dependencies.
## Acknowledgements
This project is derived from [TensorFlow.js](https://github.com/tensorflow/tfjs), the [Universal Sentence Encoder model library](https://github.com/tensorflow/tfjs-models) and [Universal Sentence Encoder Lite model weights](https://tfhub.dev/tensorflow/tfjs-model/universal-sentence-encoder-lite/1/default/1), which are also Apache 2.0 licensed.
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