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Update kaggle links to Gemma v3. Refs #911 #912

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Update kaggle links to Gemma v3. Refs #911 #912

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6 changes: 3 additions & 3 deletions README.md
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Expand Up @@ -6,7 +6,7 @@ foundation models from Google.
For additional information about Gemma, see
[ai.google.dev/gemma](https://ai.google.dev/gemma). Model weights, including
gemma.cpp specific artifacts, are
[available on kaggle](https://www.kaggle.com/models/google/gemma-2).
[available on kaggle](https://www.kaggle.com/models/google/gemma-3).

## Who is this project for?

Expand Down Expand Up @@ -34,7 +34,7 @@ portable SIMD for CPU inference.

For production-oriented edge deployments we recommend standard deployment
pathways using Python frameworks like JAX, Keras, PyTorch, and Transformers
([all model variations here](https://www.kaggle.com/models/google/gemma)).
([all model variations here](https://www.kaggle.com/models/google/gemma-3)).

## Contributing

Expand Down Expand Up @@ -104,7 +104,7 @@ winget install --id Microsoft.VisualStudio.2022.BuildTools --force --override "-
### Step 1: Obtain model weights and tokenizer from Kaggle or Hugging Face Hub

Visit the
[Kaggle page for Gemma-2](https://www.kaggle.com/models/google/gemma-2/gemmaCpp)
[Kaggle page for Gemma-2](https://www.kaggle.com/models/google/gemma-3/gemmaCpp)
and select `Model Variations |> Gemma C++`.

On this tab, the `Variation` dropdown includes the options below. Note bfloat16
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