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library_name: transformers
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DiTy/gemma-2-9b-it-function-calling

This model is a fine-tuned version of google/gemma-2-9b-it for the Function Calling task on non-synthetic data, fully annotated by humans only, on the English version of the DiTy/function-calling dataset.


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Usage (HuggingFace Transformers)

Below we share some code snippets on how to get quickly started with running the model. First, install the Transformers library with:

pip install -U transformers

Prepare your functions for Function Calling

You should write the functions (tools) used by the model in Python code and make sure to add Python docstrings as in the example below:

def get_weather(city: str):
    """
    A function that returns the weather in a given city.
    
    Args:
        city: The city to get the weather for.
    """
    import random
    
    return "sunny" if random.random() > 0.5 else "rainy"


def get_sunrise_sunset_times(city: str):
    """
    A function that returns the time of sunrise and sunset at the present moment, for a given city, in the form of a list: [sunrise_time, sunset_time].
    
    Args:
        city: The city to get the sunrise and sunset times for.
    """
    
    return ["6:00 AM", "6:00 PM"]

Using transformers


Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

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Summary

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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