Roman1111111/gpt-5.4-step-by-step-reasoning
Dataset Card for GPT-5.4-Reasoning-1500-Ultra-Logic Dataset Details Dataset Description Suggestion: I would use this to fine-tune qwen3.5 35b a3b moe, or 27b variant. However, for maximum efficiency, 2bb-20b LLMs like qwen3.5 9b and 4b, gpt-oss 20b work perfectly. Fine-tuning the newest versions (specialized reasoning variants) will yield the most significant logic jumps. This dataset is an ultra-high-density synthetic reasoning… See the full description on the dataset page: https://huggingface.co/datasets/Roman1111111/gpt-5.4-step-by-step-reasoning.
| Author / organization | Roman1111111 |
|---|---|
| License (as declared) | mit |
| Downloads | 215 (as reported by Hugging Face) |
| Likes | 77 |
| Created | 24 March 2026 |
| Last updated at source | 13 April 2026 |
Popularity, last 4 days
215 now (+19 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- mradermacher/IBM-GPT5.4-Coder-1B-GGUFModel · used to train
- mradermacher/IBM-GPT-5.4-Coder-1B-GGUFModel · used to train
- mradermacher/GemPT-26B-A4B-GGUFModel · used to train
- mradermacher/IBM-GPT5.4-Coder-1B-i1-GGUFModel · used to train
- mradermacher/IBM-GPT-5.4-Coder-1B-i1-GGUFModel · used to train
- mradermacher/GemPT-26B-A4B-i1-GGUFModel · used to train
Recent changes
- 16 Oct 2026 Description: Dataset Card for GPT-5.4-Reasoning-1500-Ultra-Logic Dataset Details Dataset Description Suggestion: I would use this to fine-tune qwen3.5 35b a3b moe, or 27b variant. However, for maximum efficiency, 2bb-20b LLMs like qwen3.5 9b and 4b, gpt → Dataset Card for GPT-5.4-Reasoning-1500-Ultra-Logic Dataset Details Dataset Description Suggestion: I would use this to fine-tune qwen3.5 35b a3b moe, or 27b variant. However, for maximum efficiency, 2bb-20b LLMs like qwen3.5 9b and 4b, gpt
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