metadata
license: mit
language:
- en
tags:
- tool-use
- function-calling
- benchmark
- quantization
- evaluation
pretty_name: QuantCall Evaluation Suite
dataset_info:
features:
- name: id
dtype: string
- name: tier
dtype: string
- name: category
dtype: string
- name: query
dtype: string
- name: tools
sequence: string
- name: ground_truth_calls
sequence: string
- name: expects_call
dtype: bool
splits:
- name: smoke_v1
num_examples: 10
QuantCall Evaluation Suite
Deterministic, versioned evaluation samples used by the QuantCall benchmark to measure how quantization degrades LLM function-calling reliability.
Contents
| File | Description |
|---|---|
data/smoke_v1.jsonl |
T0 smoke tier — 10 hand-crafted instances, always available without a GPU |
data/schemas/tool_schemas.json |
Extracted JSON Schemas for all tools in smoke_v1 |
Format
Each instance in smoke_v1.jsonl is one JSON object per line:
{
"id": "T0-001",
"tier": "T0",
"category": "simple",
"query": "What is the weather like in Paris?",
"tools": [{"name": "get_weather", "description": "...", "json_schema": {...}}],
"ground_truth_calls": [{"name": "get_weather", "arguments": {"city": "Paris"}}],
"expects_call": true
}
Versioning
Files are version-pinned (smoke_v1, smoke_v2, …). Never overwrite a pinned
version; add new versions when the evaluation set changes. This ensures all
published results remain reproducible against the exact sample they were run on.