metadata
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 to get best performance.
XAgentGen input format:
"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:
{
"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.