CodeX-7M-Non-Thinking: Instruction-Tuned Code and Text Dataset

CodeX-7M-Non-Thinking is a dataset curated from high-quality public sources and enhanced with synthetic data from both closed and open-source models. It is part of the CodeX lineup by Modotte, with a focus on providing data for model training and fine-tuning. The dataset was last updated on February 10, 2026.

Use Cases

• Fine-tuning language models for code generation based on instruction-based tuning data.
• Training models for text generation tasks using a mix of public and synthetic data sources.
• Conducting research on instruction-following capabilities in language models.
• Benchmarking model performance on tasks like question answering using curated datasets.

Strengths

• Data is curated from high-quality public sources.
• Enhanced with synthetic data from both closed and open-source models.
• Part of a lineup (CodeX) focused on providing datasets for model training.

Limitations

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

Provenance

Source

Modotte, using high-quality public sources and synthetic generation.

Collection Method

Curated from public sources and enhanced with synthetic data from models.

Time Range

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Freshness

Last updated 2026-02-10 07:22:55; freshness should be verified.

Geography

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