xLAM Function Calling 60k — LLM Agentic & Function Calling Dataset
60,000 tool-calling samples generated by Salesforce's APIGen pipeline across 3,673 executable APIs in 21 categories. Every sample passed three verification stages — format checking, actual function execution, and semantic verification — with >95% human-audited correctness. The quality benchmark for function-calling data, and the training set of the xLAM action-model family.
Dataset Details
| Provider | Salesforce |
| Category | Agentic & Function Calling |
| Size | 60k Rows |
| License | CC BY 4.0 |
| Downloads | n/a |
| Tags | Function-Calling, APIGen, Execution-Verified, Agents, 2024 |
from datasets import load_dataset
ds = load_dataset("Salesforce/xlam-function-calling-60k")
Fine-tune with this dataset
Estimated VRAM to fine-tune with QLoRA (4-bit base model + LoRA adapters), using conservative defaults:
| 7B QLoRA | ~6GB VRAM |
| 13B QLoRA | ~10GB VRAM |
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Frequently asked questions
Can I use xLAM Function Calling 60k commercially?
Yes — xLAM Function Calling 60k is released under CC BY 4.0, 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 xLAM Function Calling 60k contain, and do I need all of it?
xLAM Function Calling 60k contains 60k 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 xLAM Function Calling 60k best used for?
High-precision tool calling — every sample was verified by actually executing the API call. It belongs to the Agentic & Function Calling section of our dataset hub, where you'll find alternatives and complementary sets.
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