| --- |
| license: apache-2.0 |
| base_model: google/gemma-4-E2B-it |
| pipeline_tag: text-generation |
| library_name: rkllm |
| tags: |
| - rkllm |
| - rockchip |
| - rk3576 |
| - rk3588 |
| - gemma |
| - gemma-4 |
| --- |
| |
| # gemma-4-E2B-it-RKLLM |
|
|
| RKLLM-converted Gemma 4 E2B IT language-model artifacts for Rockchip RK3576 and RK3588 NPUs. |
|
|
| Important: the upstream Gemma 4 E2B IT model is multimodal/VLM-capable, but this repository contains only the RKLLM language-model binaries. The converted model exposed here is LLM-only: it does not accept images and does not include an RKNN vision encoder. |
|
|
| These hardware-specific `.rkllm` files require a compatible Rockchip RKLLM runtime. They are not Transformers checkpoints and cannot be loaded directly with Transformers, llama.cpp, or Ollama. |
|
|
| ## Base model |
|
|
| - Upstream model: [google/gemma-4-E2B-it](https://huggingface.co/google/gemma-4-E2B-it) |
| - License: Apache-2.0 |
| - Upstream type: VLM/multimodal |
| - RKLLM type: LLM-only |
|
|
| ## Conversion and variants |
|
|
| ### Toolkit version |
|
|
| **RKLLM Toolkit: v1.3.0** |
|
|
| Use a file built for the exact target SoC. |
|
|
| | Target | Quantization | File | SHA256 | |
| | --- | --- | --- | --- | |
| | RK3576 | W4A16 (g128) | [gemma-4-E2B-it_RK3576_w4a16_g128.rkllm](RK3576/gemma-4-E2B-it_RK3576_w4a16_g128.rkllm) | `973008fd7ebed81e2a26dcf7dcc1c28fde631837e3e021c7f3007d6e82647165` | |
| | RK3576 | W8A8 | [gemma-4-E2B-it_RK3576_w8a8.rkllm](RK3576/gemma-4-E2B-it_RK3576_w8a8.rkllm) | `b7357c01fcd51c8f896f06ee3a3746bc233031abd04e2fa0cebb5908b1382a01` | |
| | RK3588 | W8A8 | [gemma-4-E2B-it_RK3588_w8a8.rkllm](RK3588/gemma-4-E2B-it_RK3588_w8a8.rkllm) | `ae81d1e37eb54b40d2d366ef622a0c05acfb15537272e982efc1dfdd60557979` | |
|
|
| The repository also includes `gemma-4-E2B-it_data_quant.json`, used as calibration data during conversion. |
|
|
| ## Usage |
|
|
| ```bash |
| hf download HanzoHuang/gemma-4-E2B-it-RKLLM \ |
| RK3576/gemma-4-E2B-it_RK3576_w4a16_g128.rkllm \ |
| --local-dir gemma-4-E2B-it-RKLLM |
| ``` |
|
|
| Run the file with the RKLLM runtime and the upstream Gemma instruction prompt format. For Docker deployment, see [Hanzo-Huang/rkllm-docker](https://github.com/Hanzo-Huang/rkllm-docker). |
|
|
| ## Limitations |
|
|
| Vision input is not supported by these artifacts. Conversion can change output quality relative to the upstream model; validate the result on your target device. |
|
|
| ## Acknowledgements |
|
|
| Thanks to Google, Rockchip, and the RKLLM community. |
|
|
