R8 Calibration SFT: Fine-Tuning Data for Qwen3.5-9B-Derived Models

cudabenchmarktest created this dataset for fine-tuning models derived from the Qwen3.5-9B architecture. The description includes a critical warning about a required inference flag to prevent high empty-answer rates when serving models via Ollama. The dataset was last updated on April 15, 2026.

Use Cases

• Calibrating instruction-following behavior in large language models based on the dataset's intended purpose.
• Mitigating model output issues like empty responses based on the described inference warning.
• Fine-tuning models for tool use or chat applications based on the dataset's implied scope.

Strengths

• The dataset page includes a specific, critical warning about a required inference flag to prevent a 25-46% empty-answer rate.
• The dataset has a clear lineage, being intended for models derived from the Qwen3.5-9B architecture.

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 is unknown, which may limit suitability assessment.

Provenance

Source

cudabenchmarktest on Hugging Face

Freshness

Last updated 2026-04-15 04:08:20; freshness should be verified.