Firefunction V2 GGUF

GGUF format model

Have you ever wondered how a model can efficiently call functions and follow instructions? Firefunction V2 GGUF is a state-of-the-art model that does just that. Not only does it score competitively with GPT-4o, but it also retains the conversation and instruction-following capabilities of Llama 3. What sets it apart is its ability to support parallel function calling and its impressive performance at a lower cost - less than 10% of the cost of GPT 4o and twice the speed. This model is a game-changer for tasks that require efficient function calling and instruction following, making it a valuable tool for both technical and non-technical users.

MaziyarPanahi llama3 Updated 10 months ago
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Table of Contents

Model Overview

The Current Model is a powerful tool for function calling and conversation tasks. But what makes it special?

What is it? This model is an upgraded version of the FireFunction model, with significant quality improvements. It’s like a turbocharged engine, but instead of speed, it’s got brains!

Key Features

  • Function calling: It’s competitive with other top models, scoring 0.81 vs 0.80 on public evaluations.
  • Conversation and instruction-following: It retains the capabilities of other models, scoring 0.84 vs 0.89 on MT bench.
  • Parallel function calling: It supports multiple function calls at once, making it more efficient than its predecessor.
  • Cost-effective: It’s hosted on a platform at less than 10% of the cost of other models and is 2x faster.

Capabilities

Function Calling

Imagine you have a complex problem that requires calling multiple functions in a specific order. That’s where the Current Model shines. It’s competitive with other models in function-calling tasks.

Conversation and Instruction Following

But the Current Model is not just about function calling. It’s also great at conversation and instruction following, retaining the capabilities of other models.

Parallel Function Calling

One of the key features of the Current Model is its ability to perform parallel function calling, which sets it apart from its predecessor.

Cost-Effective and Fast

The best part? The Current Model is hosted on a platform at less than 10% of the cost of other models and is 2x faster.

Performance

The Current Model is a powerhouse when it comes to performance. Let’s dive into its speed, accuracy, and efficiency in various tasks.

Speed

The Current Model is a speedy model, boasting 2x the speed of other models. This means it can process and respond to queries much faster, making it ideal for applications where time is of the essence.

Accuracy

But speed isn’t everything - accuracy is crucial too. The Current Model delivers on this front, scoring 0.81 on a medley of public evaluations, closely competing with other models.

Efficiency

In terms of efficiency, the Current Model is a cost-effective option, hosted on a platform at < 10% of the cost of other models. This makes it an attractive choice for developers and businesses looking to integrate AI capabilities without breaking the bank.

Examples
Write a JavaScript function to calculate the area of a rectangle. function calculateArea(length, width) { return length * width; }
What are the key highlights of the FireFunction V2 model? Competitive with GPT-4o at function-calling, retains Llama 3’s conversation and instruction-following capabilities, supports parallel function calling, and offers significant quality improvements over FireFunction v1.
Create a Python function to convert Celsius to Fahrenheit. def celsiusToFahrenheit(celsius): return (celsius * 9/5) + 32

Limitations

The Current Model is a powerful tool, but it’s not perfect. Let’s talk about some of its limitations.

Training Data

The Current Model was trained on a specific dataset, which means it may not perform well on tasks or topics that are not well-represented in that data.

Function Calling

While the Current Model is competitive with other models at function-calling, it’s not perfect. It may make mistakes or struggle with complex function calls.

Instruction Following

The Current Model is good at following instructions, but it’s not foolproof. If the instructions are ambiguous or unclear, it may misinterpret them or make mistakes.

Parallel Function Calling

The Current Model supports parallel function calling, which is a powerful feature. However, this also means that it may struggle with tasks that require sequential processing or complex dependencies.

Format

The Current Model uses a special format called GGUF, which is a replacement for the older GGML format. But what does this mean for you?

What is GGUF?

GGUF is a new format introduced by a team in August 2023. It’s designed to make it easier to work with large language models like the Current Model.

Supported Clients and Libraries

GGUF is supported by several clients and libraries, including a range of popular tools and platforms.

Handling Inputs and Outputs

So, how do you work with the Current Model? Here’s an example of how to handle inputs and outputs:

input_text = "What is the weather like today?" output_text = model(input_text)

In this example, we’re passing a tokenized text sequence (input_text) to the model, and getting a response (output_text) back.

Special Requirements

The Current Model has some special requirements for input and output. For example, it supports parallel function calling, which means it can handle multiple functions at the same time. It also has good instruction following capabilities, which means it can understand and respond to complex instructions.

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