Bumblebee provides pre-trained Neural Network models on top of Axon. It includes integration with 🤗 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.
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:
def deps do
[
{:bumblebee, "~> 0.3.0"},
{:exla, ">= 0.0.0"}
]
end
Then configure Nx
to use EXLA backend by default in your config/config.exs
file:
import Config
config :nx, default_backend: EXLA.Backend
To use GPUs, you must set the XLA_TARGET
environment variable accordingly.
In notebooks and scripts, use the following Mix.install/2
call to both install and configure dependencies:
Mix.install(
[
{:bumblebee, "~> 0.3.0"},
{:exla, ">= 0.0.0"}
],
config: [nx: [default_backend: EXLA.Backend]]
)
To get a sense of what Bumblebee does, look at this example:
{:ok, model_info} = Bumblebee.load_model({:hf, "bert-base-uncased"})
{:ok, tokenizer} = Bumblebee.load_tokenizer({:hf, "bert-base-uncased"})
serving = Bumblebee.Text.fill_mask(model_info, tokenizer)
Nx.Serving.run(serving, "The capital of [MASK] is Paris.")
#=> %{
#=> predictions: [
#=> %{score: 0.9279842972755432, token: "france"},
#=> %{score: 0.008412551134824753, token: "brittany"},
#=> %{score: 0.007433671969920397, token: "algeria"},
#=> %{score: 0.004957548808306456, token: "department"},
#=> %{score: 0.004369721747934818, token: "reunion"}
#=> ]
#=> }
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 and the resources below.
To explore Bumblebee:
-
See examples/phoenix for single-file examples of running Neural Networks inside your Phoenix (+ LiveView) apps
-
Use Bumblebee's integration with Livebook v0.8 (or later) to automatically generate "Neural Networks tasks" from the "+ Smart" cell menu (see
kino_bumblebee
) -
For a more hands on approach, read our example notebooks
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