Semantic Router Dataset for Fine-Tuning Tool-Calling Language Models

Semantic Router Dataset is a high-quality synthetic routing dataset designed for fine-tuning small language models. The dataset, created by author nuhmanpk, trains models to select the correct tool from a dynamic pool based on a natural language user query. It was last updated on May 12, 2026.

Use Cases

• Fine-tuning language models for semantic tool selection based on user queries described in the dataset.
• Training AI agents to route to the correct tool from a dynamically changing tool pool as mentioned in the description.
• Benchmarking the performance of small language models on instruction-following and routing tasks.
• Developing and evaluating synthetic data generation methods for tool-calling applications.

Strengths

• Dataset is described as 'high-quality synthetic' and designed for fine-tuning specific small language models.
• Explicitly targets a modern AI agent task: semantic routing for tool calling.
• Last update timestamp is provided: 2026-05-12 18:26:52.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and license information are unknown, which may limit suitability assessment.

Provenance

Source

huggingface user nuhmanpk

Collection Method

Synthetic generation, likely for training purposes.

Freshness

Last updated 2026-05-12 18:26:52; freshness should be verified.