UPDATE 2023-06-06: use new syntax to configure Bert embedder.
“searching data using pre-trained models, unreal engine high quality render, 4k, glossy, vivid_colors, intricate_detail” by Stable Diffusion
Vespa can now convert text to embeddings for you automatically,
if you don’t want to bring your own vectors – but you still need to provide the ML models to use.
On Vespa Cloud we’re now making this even simpler, by also providing pre-trained models you can use for such tasks.
To take advantage of this, just pick the models you want from
cloud.vespa.ai/en/model-hub and refer
to them in your application by supplying a model-id where you would otherwise use path or url. For example:
<component id="myEmbedderId" type="bert-embedder"> <transformer-model model-id="minilm-l6-v2"/> <tokenizer-vocab model-id="bert-base-uncased"/> </component>
You can deploy this to Vespa Cloud to have these models do their job in your application –
no need to include a model in your application and wait for it to be uploaded.
You can use these models both in configurations provided by Vespa, as above, and in your own components,
with your own configurations – see the documentation for details.
We’ll grow the set of models available over time, but the models we provide on Vespa Cloud will always be an
exclusive selection of models that we think it is beneficial to use in real applications,
both in terms of performance and model quality.
We hope this will empower many more teams to leverage modern AI in their production use cases.