Llama-3.2-1B-Instruct-RKLLM

RKLLM-converted Llama 3.2 1B Instruct language-model artifacts for Rockchip RK3576 and RK3588 NPUs.

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

The upstream model is gated. Review Meta's license and acceptable-use policy before use or redistribution.

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) Llama-3.2-1B-Instruct_RK3576_w4a16_g128.rkllm bd6cbbf84e90b63d451e672a542858a5a6aa15ad2b45f83e1b5dbcd944ac3018
RK3576 W8A8 Llama-3.2-1B-Instruct_RK3576_w8a8.rkllm 9c4d103f7c486740ba75605c61a51b80d170df067645360ffad8464b50c764df
RK3588 W8A8 Llama-3.2-1B-Instruct_RK3588_w8a8.rkllm 4403aec1c018c7ebf29c95730336e848aff8824e3be3bd6be7db44b4a4973bad

The repository also includes Llama-3.2-1B-Instruct_data_quant.json, used as calibration data during conversion.

Usage

hf download HanzoHuang/Llama-3.2-1B-Instruct-RKLLM \
  RK3576/Llama-3.2-1B-Instruct_RK3576_w4a16_g128.rkllm \
  --local-dir Llama-3.2-1B-Instruct-RKLLM

Use the Llama 3.2 Instruct chat template with the RKLLM runtime. For Docker deployment, see Hanzo-Huang/rkllm-docker.

Limitations

These are target-specific converted artifacts. Validate quality, memory use, and runtime compatibility on your own Rockchip device.

Acknowledgements

Thanks to Meta, Rockchip, and the RKLLM community.

Downloads last month
36
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for HanzoHuang/Llama-3.2-1B-Instruct-RKLLM

Finetuned
(1796)
this model