Text Classification
Model2Vec
English
toolrouter
tool-routing
tool-selection
intent-classification
function-calling
static-embeddings
numpy
cpu
tiny
Eval Results (legacy)
Instructions to use stanley-nv/toolrouter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use stanley-nv/toolrouter with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("stanley-nv/toolrouter") embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everybody."]) print(embeddings.shape) - Notebooks
- Google Colab
- Kaggle
File size: 743 Bytes
b2607a3 | 1 2 3 4 5 6 7 8 9 10 11 | {
"stock_quotes": "Real-time share prices, tickers and market indices from stock exchanges.",
"smart_home": "Control lights, thermostat, locks, cameras and other connected home devices.",
"calendar": "Read, create and move meetings and appointments on the user's calendar.",
"food_delivery": "Order meals and groceries for delivery from restaurants and stores.",
"flight_search": "Search airlines for flights, fares and schedules between airports.",
"translator": "Translate words, sentences and documents from one language to another.",
"git_helper": "Run git operations: commit, push, pull, branches, diffs and history of the repository.",
"other": "No tool needed: chit-chat, writing, math, advice and general questions."
}
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