Skip to content

Commit

Permalink
Update README.md
Browse files Browse the repository at this point in the history
  • Loading branch information
josevalim authored Sep 23, 2023
1 parent 355ad10 commit 7302867
Showing 1 changed file with 12 additions and 16 deletions.
28 changes: 12 additions & 16 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -5,10 +5,20 @@

Bumblebee provides pre-trained Neural Network models on top of [Axon](https://github.com/elixir-nx/axon). It includes integration with [🤗 Models](https://huggingface.co/models), allowing anyone to download and perform Machine Learning tasks with few lines of code.

To see all supported architectures, [check out our documentation sidebar](https://hexdocs.pm/bumblebee).

![Numbat and Bumblebees](.github/images/background.jpg)

## Getting started

The best way to get started with Bumblebee is with [Livebook](https://livebook.dev). [Our announcement video](https://news.livebook.dev/announcing-bumblebee-gpt2-stable-diffusion-and-more-in-elixir-3Op73O) shows how to use Livebook's Smart Cells to perform different Neural Network tasks with few clicks. You can then tweak the code and deploy it.

![](.github/images/kino_bumblebee_token_classification.png)

We also provide single-file examples of running Neural Networks inside your Phoenix (+ LiveView) apps inside the [examples/phoenix](examples/phoenix) folder.

![](.github/images/phx_image_classification.png)

You may also check [our official docs](https://hexdocs.pm/bumblebee), which includes notebooks and our API reference. The "Tasks" section in the sidebar covers high-level APIs for using Bumblebee. The remaining modules in the sidebar lists all supported architectures.

## Installation

First add Bumblebee and EXLA as dependencies in your `mix.exs`. EXLA is an optional dependency but an important one as it allows you to compile models just-in-time and run them on CPU/GPU:
Expand Down Expand Up @@ -67,20 +77,6 @@ Nx.Serving.run(serving, "The capital of [MASK] is Paris.")

We load the BERT model from Hugging Face Hub, then plug it into an end-to-end pipeline in the form of "serving", finally we use the serving to get our task done. For more details check out [the documentation](https://hexdocs.pm/bumblebee) and the resources below.

## Examples

To explore Bumblebee:

* See [examples/phoenix](examples/phoenix) for single-file examples of running Neural Networks inside your Phoenix (+ LiveView) apps

![](.github/images/phx_image_classification.png)

* Use Bumblebee's integration with Livebook v0.8 (or later) to automatically generate "Neural Networks tasks" from the "+ Smart" cell menu (see [`kino_bumblebee`](https://github.com/livebook-dev/kino_bumblebee))

![](.github/images/kino_bumblebee_token_classification.png)

* For a more hands on approach, read our example [notebooks](notebooks)

## License

Copyright (c) 2022 Dashbit
Expand Down

0 comments on commit 7302867

Please sign in to comment.