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10 changes: 5 additions & 5 deletions site/en/hub/overview.md
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Expand Up @@ -2,10 +2,10 @@
# TensorFlow Hub

TensorFlow Hub is an open repository and library for reusable machine learning.
The [tfhub.dev](https://tfhub.dev) repository provides many pre-trained models:
[Kaggle Models](https://www.kaggle.com/models) provides many pre-trained models:
text embeddings, image classification models, TF.js/TFLite models and much more.
The repository is open to
[community contributors](https://tfhub.dev/s?subtype=publisher).
[community contributors](https://www.kaggle.com/models?owner-type=user).

The [`tensorflow_hub`](https://github.com/tensorflow/hub) library lets you
download and reuse them in your TensorFlow program with a minimum amount of
Expand All @@ -14,7 +14,7 @@ code.
```python
import tensorflow_hub as hub

model = hub.KerasLayer("https://tfhub.dev/google/nnlm-en-dim128/2")
model = hub.KerasLayer("https://www.kaggle.com/models/google/nnlm/TensorFlow2/en-dim128/2")
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@jorgeorpinel jorgeorpinel May 7, 2025 •
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Note: I based this on the example in https://www.kaggle.com/models/google/nnlm but did not confirm whether this specific block code works.

embeddings = model(["The rain in Spain.", "falls",
"mainly", "In the plain!"])

Expand All @@ -23,8 +23,8 @@ print(embeddings.shape) #(4,128)

## Next Steps

- [Find models on tfhub.dev](https://tfhub.dev)
- [Publish models on tfhub.dev](publish.md)
- [Find models on kaggle.com](https://www.kaggle.com/models)
- [Publish models on kaggle.com](publish.md)
- TensorFlow Hub library
- [Install TensorFlow Hub](installation.md)
- [Library overview](lib_overview.md)
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