Instructions to use HanzoHuang/MiniCPM4-0.5B-RKLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- RKLLM
How to use HanzoHuang/MiniCPM4-0.5B-RKLLM with RKLLM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Document RKLLM artifacts and checksums
Browse files
README.md
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---
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license: apache-2.0
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base_model: openbmb/MiniCPM4-0.5B
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pipeline_tag: text-generation
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library_name: rkllm
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tags:
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- rkllm
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- rockchip
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- rk3576
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- rk3588
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- minicpm4
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---
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# MiniCPM4-0.5B-RKLLM
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RKLLM-converted MiniCPM4-0.5B language-model artifacts for Rockchip RK3576 and RK3588 NPUs.
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These files are hardware-specific `.rkllm` binaries. They are not Transformers checkpoints and require a compatible Rockchip RKLLM runtime; they cannot be loaded directly with Transformers, llama.cpp, or Ollama.
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## Base model
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- Upstream model: [openbmb/MiniCPM4-0.5B](https://huggingface.co/openbmb/MiniCPM4-0.5B)
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- License: Apache-2.0
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- Model type: LLM (text only)
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## Conversion and variants
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Converted with RKLLM Toolkit 1.3.0. Use a file built for the exact target SoC.
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| Target | Quantization | File | SHA256 |
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| --- | --- | --- | --- |
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| RK3576 | W4A16 (g128) | [MiniCPM4-0.5B_RK3576_w4a16_g128.rkllm](RK3576/MiniCPM4-0.5B_RK3576_w4a16_g128.rkllm) | `34060c78f36ee6ac2a772d5353d32d700fe940ea48564f083b8665a85fdc499c` |
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| RK3576 | W8A8 | [MiniCPM4-0.5B_RK3576_w8a8.rkllm](RK3576/MiniCPM4-0.5B_RK3576_w8a8.rkllm) | `10f2bfa298b5a79077fc52f339ead0446e9e834632226a8bfcc3d003d42a0ba8` |
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| RK3588 | W8A8 | [MiniCPM4-0.5B_RK3588_w8a8.rkllm](RK3588/MiniCPM4-0.5B_RK3588_w8a8.rkllm) | `fef1e215dfa69391d2c5da53eb918020419a71e6b3539d9ef91d56d956b602ea` |
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The repository also includes `MiniCPM4-0.5B_data_quant.json`, used as calibration data during conversion.
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## Usage
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Download a matching artifact with the [Hugging Face CLI](https://huggingface.co/docs/huggingface_hub/guides/cli):
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```bash
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hf download HanzoHuang/MiniCPM4-0.5B-RKLLM \
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RK3576/MiniCPM4-0.5B_RK3576_w4a16_g128.rkllm \
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--local-dir MiniCPM4-0.5B-RKLLM
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```
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Run it with the RKLLM runtime and the upstream MiniCPM4 chat template. For a Docker deployment, see [Hanzo-Huang/rkllm-docker](https://github.com/Hanzo-Huang/rkllm-docker).
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## Limitations
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Conversion can change output quality relative to the upstream model. Runtime, driver, memory, and toolkit compatibility depend on the Rockchip software stack installed on the device.
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## Acknowledgements
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Thanks to OpenBMB, Rockchip, and the RKLLM community.
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