---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tool-bert
  results: []
---

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# tool-bert

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased).

It uses a custom made dataset of sample user instructions, which are classified to a number of possible local assistant function calling endpoints. 

For example, given an input query, tool-bert returns a prediction as to what tool to use to augment a downstream LLM generated output with. 

More information on these tools to follow, but example tools are "play music", "check the weather", "get the news", "take a photo", or use no tool. 

Basically, this model is meant to be a means of allowing very small LLMs (i.e. 8B and below) to use function calling. 

All limitations and biases are inherited from the parent model. 

### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1