Instructions to use litert-community/decider-0.8b-LiteRT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use litert-community/decider-0.8b-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=litert-community/decider-0.8b-LiteRT \ --prompt="Write me a poem"
- LiteRT
How to use litert-community/decider-0.8b-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
File size: 1,018 Bytes
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"state": {
"ticket": "I was charged twice for order ZVX-104. Please refund the duplicate payment. The first payment was correct.",
"customer_tier": "basic",
"history": [
{
"step": 1,
"event": "Request received"
},
{
"step": 2,
"event": "No prior complaint"
}
]
},
"questions": {
"team": {
"type": "choice",
"instructions": "Which team should handle this ticket?",
"criteria": {
"billing": "Charges, invoices, payments, refunds",
"technical": "Software errors, outages, broken features",
"accounts": "Login, passwords, account access",
"other": null
}
},
"refund_requested": {
"type": "noul",
"instructions": "Does the customer ask for a refund?"
},
"frustration": {
"type": "score",
"instructions": "How frustrated is the customer?",
"criteria": [
"calm",
"frustrated",
"very frustrated"
]
}
}
}
|