README.md

---
library_name: recurrentgemma
license: gemma
license_link: https://ai.google.dev/gemma/terms
pipeline_tag: text-generation
tags:
- jax
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extra_gated_prompt: To access RecurrentGemma 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
---

# RecurrentGemma Model Card

**Model Page**: [RecurrentGemma](https://ai.google.dev/gemma/docs)

> [!IMPORTANT]
>
> This repository corresponds to the research [RecurrentGemma repository](https://github.com/google-deepmind/recurrentgemma) in Jax.

This model card corresponds to the 2B instruct version of the RecurrentGemma model for usage with flax. For more information about the model, visit https://huggingface.co/google/recurrentgemma-2b-it.

**Resources and Technical Documentation**:

* [Responsible Generative AI Toolkit](https://ai.google.dev/responsible)
* [Gemma on Kaggle](https://www.kaggle.com/models/google/gemma)
* [Gemma on Vertex Model Garden](https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/335)

**Terms of Use**: [Terms](https://www.kaggle.com/models/google/recurrentgemma/license/consent/verify/huggingface?returnModelRepoId=google/recurrentgemma-2b-it-flax)

**Authors**: Google

## Loading the model

To download the weights and tokenizer, run:

```python
from huggingface_hub import snapshot_download

local_dir = snapshot_download(repo_id="google/recurrentgemma-2b-it-flax")
snapshot_download(repo_id="google/recurrentgemma-2b-it-flax", local_dir=local_dir)
```

Then download [this script](https://github.com/google-deepmind/gemma/blob/main/examples/sampling.py) from the [gemma GitHub repository](https://github.com/google-deepmind/gemma) and call `python sampling.py` with the `--path_checkpoint` and `--path_tokenizer` arguments pointing to your local download path.