Glaive Function Calling v2 — LLM Agentic & Function Calling Dataset
The standard open function-calling SFT dataset: ~113k conversations (112,960 rows) where a system prompt defines available JSON function schemas and the assistant learns when to call them, when to answer directly, and how to handle function responses. The foundation that countless open tool-calling fine-tunes (and cleaned derivatives like Hermes) build on.
Dataset Details
Provider
Glaive AI
Category
Agentic & Function Calling
Size
113k Rows
License
Apache 2.0
Downloads
n/a
Tags
Function-Calling, Tool-Use, JSON, Agents
from datasets import load_dataset
ds = load_dataset("glaiveai/glaive-function-calling-v2")
Fine-tune with this dataset
Estimated VRAM to fine-tune with QLoRA (4-bit base model + LoRA adapters), using conservative defaults:
xLAM Function Calling 60k — High-precision tool calling — every sample was verified by actually executing the API call
Hermes Function Calling v1 — Models that must return valid structured JSON — for agents, extraction, and tool pipelines
Frequently asked questions
Can I use Glaive Function Calling v2 commercially?
Yes — Glaive Function Calling v2 is released under Apache 2.0, a permissive license that allows commercial use, including training models you ship in a product. Check the dataset card for attribution requirements before release.
How much data does Glaive Function Calling v2 contain, and do I need all of it?
Glaive Function Calling v2 contains 113k Rows. You rarely need all of it: for style and format fine-tuning, a few hundred to a few thousand examples are enough — load a slice (e.g. split="train[:1000]") and scale up only if quality plateaus.
What is Glaive Function Calling v2 best used for?
Teaching a model basic function-calling: when to call, what JSON to emit, how to use results. It belongs to the Agentic & Function Calling section of our dataset hub, where you'll find alternatives and complementary sets.