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
Download web/model.bin from stanley-nv/toolrouter: direct link, hf CLI and curl.
- Browser
- Download file 9.54 MB
-
https://huggingface.co/stanley-nv/toolrouter/resolve/main/web/model.bin
- Command line
-
hf download hf://stanley-nv/toolrouter/web/model.bin
-
curl -L -o model.bin https://huggingface.co/stanley-nv/toolrouter/resolve/main/web/model.bin
9.54 MB
- Xet hash:
- e060d362074e3913a88dd8a58817b873ef7078bb2264a50cee24a745c48cca43
- Size of remote file:
- 9.54 MB
- SHA256:
- 0c636117534c9527cac997367f21017b668ad1f79bbbcd1f90c385521e4fe1ac
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