Upgrade card: rich YAML metadata (tags/language/configs), schema docs, load_dataset quickstart
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README.md
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---
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license: apache-2.0
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---
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# ⚡ Professional Japanese Function Calling Dataset for LLM Alignment (Free Trial)
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- **Schema Stability:** 100% schema‑validated — no phantom tool‑calls, no argument‑type mismatches, no malformed trajectories.
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- **Robust Error Recovery:** Enforces multi-turn execution resilience against high-context Japanese tool routing, honorific variations, and entity double-meanings without structural breakdown.
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---
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## 🚀 Upgrade to Production Scale & Commercial Tiers
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---
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license: apache-2.0
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language:
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- ja
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pretty_name: Japanese Function Calling Dataset (50-Row Free Trial)
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tags:
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- function-calling
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- tool-use
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- agents
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- japanese
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- synthetic
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task_categories:
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- text-generation
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size_categories:
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- n<1K
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data.jsonl
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---
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# ⚡ Professional Japanese Function Calling Dataset for LLM Alignment (Free Trial)
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- **Schema Stability:** 100% schema‑validated — no phantom tool‑calls, no argument‑type mismatches, no malformed trajectories.
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- **Robust Error Recovery:** Enforces multi-turn execution resilience against high-context Japanese tool routing, honorific variations, and entity double-meanings without structural breakdown.
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**Schema (per row):** Single-shot design — a Japanese user request followed by a strict-JSON tool call (optimized for high-precision JA tool-routing alignment).
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```json
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{
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"id": "unique sample identifier",
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"tools": "JSON string: array of available tool definitions (name, description, parameters)",
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"conversations": [
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{"from": "user", "value": "日本語のタスク依頼"},
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{"from": "assistant", "value": "tool call as strict JSON"}
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]
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}
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```
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**Load with 🤗 Datasets:**
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```python
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from datasets import load_dataset
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ds = load_dataset("springofwindslabs/function-calling-ja-trial", split="train")
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print(ds[0]["conversations"])
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```
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---
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## 🚀 Upgrade to Production Scale & Commercial Tiers
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