Instructions to use mlboydaisuke/TwIL-LM3-LiteRT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use mlboydaisuke/TwIL-LM3-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/TwIL-LM3-LiteRT \ --prompt="Write me a poem"
- LiteRT
How to use mlboydaisuke/TwIL-LM3-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
Commit History
3 days ago
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Thinking cannot be switched off, and the think tags come back inside the text: litert-lm 0.18.0 (measured 2026-10-13)
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25 days ago
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Chat template: accept the 0.18 content-parts form (string form unchanged); weights, tokenizer and executor metadata byte-identical
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Card: base_model_relation: quantized (so the conversion lists under the base model's Quantizations, not Finetunes)
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Card: restore the section dropped by the 2026-08 note script (text after 'Conversion notes')
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Card: note the default-system-prompt fix (weights unchanged)
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Restore the vendor's default system prompt in the chat template (weights unchanged). The converter's template probe never renders the block the upstream template emits when the caller sends no system message, so the bundle silently dropped it; with no system message the prompt now renders byte-identical to the upstream chat template's output (see the card note).
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card: the formal-logic A/B against the base - 10/12 vs 9/12, no difference detected
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TwIL-LM3 int4 (blockwise-32 + OCTAV, externalised embedder)
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TwIL-LM3 LiteRT-LM card
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webAI Non-Commercial License v1.0 (required by its SS3.1)
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initial commit
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