Instructions to use litert-community/Shieldstral-1.0-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use litert-community/Shieldstral-1.0-3B 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=litert-community/Shieldstral-1.0-3B \ --prompt="Write me a poem"
- LiteRT
How to use litert-community/Shieldstral-1.0-3B 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
Chat template: accept the 0.18 content-parts form (string form unchanged); weights, tokenizer and executor metadata byte-identical
4a48b53 verified Download Shieldstral-1.0-3B-vision_int4.litertlm from litert-community/Shieldstral-1.0-3B: direct link, hf CLI and curl.
- Browser
- Download file 2.78 GB
-
https://huggingface.co/litert-community/Shieldstral-1.0-3B/resolve/main/Shieldstral-1.0-3B-vision_int4.litertlm
- Command line
-
hf download hf://litert-community/Shieldstral-1.0-3B/Shieldstral-1.0-3B-vision_int4.litertlm
-
curl -L -o Shieldstral-1.0-3B-vision_int4.litertlm https://huggingface.co/litert-community/Shieldstral-1.0-3B/resolve/main/Shieldstral-1.0-3B-vision_int4.litertlm
2.78 GB
- Xet hash:
- 69e5042fdef5c36974455e36d374a18528eba70aeba4621b859674477be57589
- Size of remote file:
- 2.78 GB
- SHA256:
- 3f9289463889fe1232da2bee6ab133804b3e5a381808b00dc1b29e9e36b877bc
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