CleverBoi: A Multi-Source Instruction Dataset for Logic and Code

CleverBoi aggregates several datasets focused on logic, inference, empathy, math, and coding into a unified Alpaca instruction format. The collection was created by user 'theprint' and last updated on August 26, 2024. Its constituent datasets include LogicInference_OA, Evol-Instruct-Python-26k, Open-Platypus, and python_code_instructions_18k_alpaca.

Use Cases

• Fine-tuning language models for instruction-following based on the Alpaca format mentioned in the description
• Training models on logical inference tasks based on the LogicInference_OA source
• Improving code generation capabilities based on the Evol-Instruct-Python-26k and python_code_instructions_18k_alpaca sources
• Enhancing mathematical reasoning based on the Open-Platypus source

Strengths

• Formatted to follow the Alpaca instruction-following format, which is a standard for fine-tuning
• Integrates multiple established source datasets, including LogicInference_OA and Evol-Instruct-Python-26k
• Last updated on 2024-08-26, indicating recent maintenance

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 and total size are unknown, which may limit suitability assessment

Provenance

Source

Aggregated from multiple Hugging Face datasets: KK04/LogicInference_OA, mlabonne/Evol-Instruct-Python-26k, garage-bAInd/Open-Platypus, iamtarun/python_code_instructions_18k_alpaca

Collection Method

Curated and reformatted by the author 'theprint'

Freshness

Last updated 2024-08-26 19:30:16