PersianDatasets2: Structured Persian Data for Instruction Tuning of Large Language Models

PersianDatasets2 is a Persian-language dataset designed for training conversational artificial intelligence models. The dataset is structured for instruction tuning and supervised fine-tuning, with examples formatted as Instruction → Input → Output. It was created by author kasranaqhdpur and last updated on Hugging Face on 2026-07-11.

Use Cases

• Instruction tuning of Persian LLMs based on the structured instruction-response format.
• Supervised fine-tuning for conversational AI based on the described instruction-following examples.
• Benchmarking model performance on Persian language tasks based on the described dataset purpose.

Strengths

• Data is structured specifically for modern LLM training with an Instruction → Input → Output format.
• Dataset is explicitly designed for the concrete tasks of instruction tuning and supervised fine-tuning.

Limitations

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

Provenance

Source

kasranaqhdpur on Hugging Face

Collection Method

Likely gathered or created for instruction tuning purposes; method not specified.

Time Range

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Freshness

Last updated 2026-07-11 15:53:36; freshness should be verified.

Geography

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