| --- |
| library_name: keras-hub |
| license: gemma |
| license_link: https://ai.google.dev/gemma/terms |
| pipeline_tag: text-generation |
| extra_gated_heading: Access Gemma 1.1 on Hugging Face |
| extra_gated_prompt: To access Gemma 1.1 on Hugging Face, you’re required to review |
| and agree to Google’s usage license. To do this, please ensure you’re logged-in |
| to Hugging Face and click below. Requests are processed immediately. |
| extra_gated_button_content: Acknowledge license |
| --- |
| |
| # Gemma 1.1 |
|
|
| **Google Model Page**: [Gemma](https://ai.google.dev/gemma/docs) |
|
|
| This model card corresponds to the latest 2B instruct version of the Gemma 1.1 model in Keras. |
|
|
| Keras models can be used with JAX, PyTorch or TensorFlow as numerical backends. |
| JAX, with its support for SPMD model paralellism, is recommended for large models. |
| For more information: [distributed training with Keras and JAX](https://keras.io/guides/distribution/). |
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|
| You can find other models in the Gemma family here: |
|
|
| | | Base | Instruct | |
| |----|----------------------------------------------------|----------------------------------------------------------------------| |
| | 2B | [gemma-2b-keras](https://huggingface.co/google/gemma-2b-keras) | [**gemma-1.1-2b-it-keras**](https://huggingface.co/google/gemma-1.1-2b-it-keras) | |
| | 7B | [gemma-7b-keras](https://huggingface.co/google/gemma-7b-keras) | [gemma-1.1-7b-it-keras](https://huggingface.co/google/gemma-1.1-7b-it-keras) | |
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| For more information about the model, visit https://huggingface.co/google/gemma-1.1-2b-it. |
|
|
| Model Page |
| : [Gemma](https://ai.google.dev/gemma/docs/gemma) |
|
|
| Resources and Technical Documentation |
| : [Technical Report](https://goo.gle/gemma) |
| : [Responsible Generative AI Toolkit](https://ai.google.dev/responsible) |
|
|
| Terms of Use |
| : [Terms](https://www.kaggle.com/models/google/gemma/license/consent/verify/huggingface?returnModelRepoId=google/gemma-1.1-2b-it-keras) |
|
|
| Authors |
| : Google |
|
|
| ## Loading the model |
|
|
| ```python |
| import keras_nlp |
| |
| gemma_lm = keras_nlp.models.GemmaCausalLM.from_preset("hf://google/gemma-1.1-2b-it-keras") |
| ``` |
