Instructions to use litert-community/MiniCPM5-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use litert-community/MiniCPM5-2B with LiteRT:
# 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
Card: int8 file rebuilt with the models/minicpm5 README command (dynamic_wi8_afp32)
Thanks for the go-ahead on adopting the README-command int8 (the 09-12 thread). This PR replaces MiniCPM5-2B_int8.litertlm with the bundle the LiteRT-LM models/minicpm5/README.md command produces with --quantization_recipe=dynamic_wi8_afp32 on the released litert-torch 0.9.4 (2,546,937,984 bytes, sha256 61dafe88β¦), and rewrites the card and litertlm_manifest.json so they describe that file: the canonical template (direct answers unless the app turns thinking on), one 128-token prefill signature, in-graph int8 embedding and lm_head, and the rows measured on it. The int4 file is unchanged (blockwise-32 with the in-place epsilon on its 13 dead rows; the payload under those scales is inert β GSM8K 87 with the same misses on a payload-zeroed copy).
What the new file measured: GSM8K thinking-off 93 (bf16 92) on the Mac GPU; the 8-question gate 6/8 at its no-think default (the bf16 model's own thinking-off score) and 8/8 with thinking on, both backends; Mac M4 Max 2084 / 124.2 tok/s on the GPU and 175 / 37.1 on the CPU; Galaxy S26 full OpenCL delegation (1836/1836 + 1655/1655) with 542β549 / 22.4β22.6 tok/s on the GPU and 93β132 / 15.1β18.2 on the CPU (v0.16.0 kit, cooled and uncapped before each run). The previous int8's fp32-activation declaration is not needed here: this file passes the thinking-on gate on the GPU with the runtime's default fp16 activations.
PR #4 (the iOS entitlement wording and the per-signature node counts) is folded in; if this one lands I will close #4. If any of it does not fit the card, close it and I will carry it elsewhere. Thanks.
Links β the conversion command: https://github.com/google-ai-edge/LiteRT-LM/blob/main/models/minicpm5/README.md#model-conversion Β· the pbtext the file was built with: https://github.com/google-ai-edge/LiteRT-LM/blob/b5e34ab1/models/minicpm5/LlmMetadataProto.pbtext Β· the runtime: https://github.com/google-ai-edge/litert
cc @Yoursmiling
I merged another PR before seeing this comment π , so you need resolve the conflict first