jddqd/xlam-toolace-sft

xlam + toolace: function calling, prepared for SFT

The union of these prepared datasets, same format and processing (see each one's card):

• xlam (jddqd/xlam-function-calling-60k-sft): from Salesforce/xlam-function-calling-60k (revision 26d14ebfe18b1f7b524bd39b404b50af5dc97866), licensed CC-BY-4.0 by Salesforce. Please cite the original APIGen / xLAM work.
• toolace (jddqd/toolace-sft): from Team-ACE/ToolACE (revision 6bda777c88d21e5a204703c1ee45597a8fa4f734), licensed Apache-2.0 by Team-ACE. Please cite the original ToolACE work.

Each row keeps the license of its source dataset: cite the original works when using this data.

Each line is a conversation: messages in the Hugging Face chat format, tools in the exact function-doc format the BFCL evaluation puts in the prompt. Usable with tokenizer.apply_chat_template(messages, tools=tools):

{
  "messages": [
    {
      "role": "user",
      "content": "What is the weather in Paris?"
    },
    {
      "role": "assistant",
      "content": "",
      "tool_calls": [
        {
          "type": "function",
          "function": {
            "name": "get_weather",
            "arguments": {
              "city": "Paris"
            }
          }
        }
      ]
    }
  ],
  "tools": [
    {
      "name": "get_weather",
      "description": "Get the current weather of a city. Note that the provided function is in Python 3 syntax.",
      "parameters": {
        "type": "dict",
        "properties": {
          "city": {
            "type": "string",
            "description": "The city name."
          },
          "unit": {
            "type": "string",
            "description": "celsius or fahrenheit.",
            "default": "celsius"
          }
        },
        "required": [
          "city"
        ]
      }
    }
  ]
}

Combination

Each source keeps its own train / validation split (the validation set is the union of the sources' validation sets). Exact duplicates across sources are kept once (in the first source listed), and a validation conversation found in another source's train set is dropped. Rows are shuffled (seed 0).

source	train	validation	train tokens
xlam	55,627	1,721	30,327,357
toolace	10,346	320	7,058,903

dropped	rows
none	0

Statistics

category	train	validation
parallel_multiple	21,451	664
multiple	20,846	645
parallel	12,492	386
simple	8,998	278
no_call	1,491	46
multi_turn	695	22