Instructions to use mlboydaisuke/MiniCPM5-2B-LiteRT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use mlboydaisuke/MiniCPM5-2B-LiteRT with LiteRT-LM:
# LiteRT-LM runs on various platforms (Android, iOS, Windows, Linux, macOS, IoT, Web/WASM) # and supports many APIs (C++, Python, Kotlin, Swift, JavaScript, Flutter). # For platform-specific integration guides, please refer to the official developer website: # https://ai.google.dev/edge/litert-lm # To try LiteRT-LM, the easiest way is to use our CLI tool. # 1. Install the LiteRT-LM CLI tool: pip install -U litert-lm # 2. Download and run this model locally: # See: https://ai.google.dev/edge/litert-lm/cli # A single .litertlm file in the repo is picked automatically; otherwise the CLI asks which one to run # (or pass its name right after the repo id). litert-lm run \ --from-huggingface-repo=mlboydaisuke/MiniCPM5-2B-LiteRT \ --prompt="Write me a poem"
- LiteRT
How to use mlboydaisuke/MiniCPM5-2B-LiteRT 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: add a note on litert-lm's 10-minute send_message timeout
Browse files
README.md
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@@ -75,6 +75,7 @@ Since the 2026-10-13 re-pack the default is a **direct answer**: the bundled tem
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- `enable_thinking=false` (via `ThinkingConfig` or the conversation's extra context — both reach the template) switches the model to **direct answers**: two- to seven-token replies on the gate questions, ~10× faster turns, and the GSM8K numbers above. `enable_thinking=true` pre-fills the think opener explicitly.
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- Sampling: OpenBMB recommends `temperature 1.0, top_p 0.95`; the gates above are greedy.
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- Prompt format is ChatML (`<|im_start|>role\n…<|im_end|>\n`), 4096-token KV budget, six prefill signatures (1024, 256, 64, 16, 4, 1).
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## Performance
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- `enable_thinking=false` (via `ThinkingConfig` or the conversation's extra context — both reach the template) switches the model to **direct answers**: two- to seven-token replies on the gate questions, ~10× faster turns, and the GSM8K numbers above. `enable_thinking=true` pre-fills the think opener explicitly.
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- Sampling: OpenBMB recommends `temperature 1.0, top_p 0.95`; the gates above are greedy.
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- Prompt format is ChatML (`<|im_start|>role\n…<|im_end|>\n`), 4096-token KV budget, six prefill signatures (1024, 256, 64, 16, 4, 1).
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- **Replies that take over 10 minutes.** On litert-lm 0.18.x and 0.19.0, a blocking `send_message` that is still generating after 10 minutes fails with `DEADLINE_EXCEEDED` (a fixed timeout with no setting), and the generation it leaves running can crash the process. For long replies on a slow backend (long thinking in particular), lower `max_output_tokens` or use the streaming `send_message_async`, which has no such limit.
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## Performance
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