Instructions to use jedick/functiongemma-langcalc-en.zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use jedick/functiongemma-langcalc-en.zh 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=jedick/functiongemma-langcalc-en.zh \ --prompt="Write me a poem"
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from jedick/functiongemma-langcalc-en.zh: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/jedick/functiongemma-langcalc-en.zh/resolve/main/tokenizer.json
- Command line
-
hf download hf://jedick/functiongemma-langcalc-en.zh/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/jedick/functiongemma-langcalc-en.zh/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- 74f7059f05cfcc5dc6a2016f18c62e60e864f3dfefd2b33bdc4a8d55effed320
- Size of remote file:
- 33.4 MB
- SHA256:
- 80d7f800b949accd7eb940bac75e642f9468e4df157403032a55bf54ed23b650
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