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README.md
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| Validation | All trajectories verified against live tool executors |
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| Supported benchmarks | BFCL v4 Multi-Turn, τ²-bench |
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## Intended Use
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- Supervised fine-tuning (SFT) of agentic language models for multi-turn tool use
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- Training models to ground tool arguments in verifiable context rather than hallucinating values
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- Evaluation of long-horizon tool-calling capabilities
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## Reference Training Setup
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The dataset was originally used to train a 4B parameter model via pure SFT (no RL):
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- Base model: Qwen3-4B-Instruct
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| Validation | All trajectories verified against live tool executors |
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| Supported benchmarks | BFCL v4 Multi-Turn, τ²-bench |
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## Reference Training Setup
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The dataset was originally used to train a 4B parameter model via pure SFT (no RL):
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- Base model: Qwen3-4B-Instruct
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