---
license: apache-2.0
tags:
- function call
---
XAgentLLaMa is a collection of fine-tuned generative text models ranging in scale from 7 billion to 34 billion based on Llama 2 and Code Llama.
This is the repository for the 34B fine-tuned model, optimized for XAgent with strong function call ability.

## Warning: This is a preview version of the model, does not stand for final quality.

We collect around 300K pieces of data and fine-tune Code-Llama 34B with 48 A100 GPUs. More details will be released later.

This model is trained with a special function call format, and should be used with [XAgentGen](https://github.com/OpenBMB/XAgent/tree/dev/XAgentGen) to get best performance.

### XAgentGen input format:
```json
"messages":[
    {
    "role":"system",
    "content":"...."
    },
    {...}
],
"global_arguments":{ // Optional
    "type": "object",
    "properties":{
        "k1":{
            "type":"integer",
            "description":"..."
        },
        "k2":{
            "type":"string",
            "description":"..."
        },
        ...
    },
    "required":["k1","k2"]
},
"functions":[// Optional
    {
        "name":"func1",
        "description":"...",
        "parameters":{
            "type":"object",
            "properties":{...},
            "required":[...]
        }
    },
    ....
],
"function_call": {// Optional
    "name":"func1"
}
```

### XAgentGen call output format:
```json
{
    "global_arguments": {
        "k1":"v1",
        "k2":"v2",
        "k3":"v3",
        ...
    },
    "function_call":{
        "name":"func1",
        "arguments":{...}
    }
}
```
If the json format of `global_arguments` is provided, the output will contains the `global_arguments` at any time.