Add dataset card

README.md

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+---
+language:
+- en
+license: apache-2.0
+size_categories:
+- 100K<n<1M
+task_categories:
+- text-generation
+pretty_name: Hard Instruction Following SFT (100K)
+tags:
+- instruction-following
+- multi-constraint
+- sft
+- supervised-fine-tuning
+- format-following
+- ifeval
+- constraint-satisfaction
+- synthetic
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: instruction-following-hard-sft-100k.jsonl
+---
+
+# Hard Instruction Following SFT (100K)
+
+100,000 ShareGPT conversations where the assistant correctly satisfies multiple simultaneous explicit constraints in a single response. Each example pairs a multi-constraint prompt with a response that honors every constraint without dropping any.
+
+Targets the instruction-following capability measured by IFEval and similar benchmarks.
+
+## Motivation
+
+A key failure mode in deployed LLMs is dropping constraints under load — responding to a multi-requirement prompt by satisfying some requirements while silently ignoring others. When a user says "write exactly 3 bullet points, each under 15 words, professional tone, mention X, don't mention Y," models often:
+
+- Write 4 or 5 bullets when told exactly 3
+- Exceed the word limit on some bullets
+- Forget the exclusion constraint
+- Drift from the specified tone
+
+This dataset trains models to track and honor all constraints simultaneously.
+
+## Dataset Description
+
+**100,000 conversations** across 21 prompt scenarios, each with 4-6 simultaneous constraints:
+
+### Constraint Count Distribution
+
+| Constraints per prompt | Count | % |
+|---|---|---|
+| 4 | ~31,800 | 32% |
+| 5 | ~50,000 | 50% |
+| 6 | ~18,200 | 18% |
+
+### Constraint Types Covered
+
+| Type | Description |
+|---|---|
+| `format` | Output structure (bullets, table, numbered list, prose) |
+| `length` | Exact or maximum word/sentence/item counts |
+| `tone` | Register (formal, casual, professional, academic, motivating) |
+| `content` | Specific topics or elements that must appear |
+| `exclusion` | Specific words, topics, or elements that must NOT appear |
+| `structure` | Internal organization (SBI format, chronological, paragraph role) |
+| `style` | Voice, persona, or rhetorical approach |
+| `order` | Sequence constraints (X must come first, end with Y) |
+| `audience` | Target reader expertise level |
+| `persona` | Signature, role, or POV requirements |
+
+### Task Domains
+
+Product writing, email drafting, code explanation, educational content, social media, academic writing, performance reviews, technical documentation, meeting facilitation, recipe/how-to guides, creative writing.
+
+## Format
+
+```json
+{
+  "conversations": [
+    {
+      "from": "human",
+      "value": "Write a product description for a standing desk. Requirements: exactly 3 bullet points, each bullet under 15 words, professional tone, mention adjustable height and ergonomics, do NOT mention price or any specific brand name."
+    },
+    {
+      "from": "gpt",
+      "value": "- Adjustable height lets you alternate between sitting and standing throughout your workday.\n- Ergonomic design reduces back strain and promotes healthier posture over long hours.\n- Smooth, quiet motor enables quick transitions so you stay focused and productive."
+    }
+  ],
+  "metadata": {
+    "constraint_count": 5,
+    "constraint_types": ["format", "length", "tone", "content", "exclusion"]
+  },
+  "id": "abc123"
+}
+```
+
+## Key Properties of Correct Responses
+
+**1. Complete constraint satisfaction**: Every constraint in the prompt is honored in the response. No silent omissions.
+
+**2. Verification-friendly outputs**: Responses are structured so constraints can be audited — exact bullet counts, verifiable word counts, no excluded terms.
+
+**3. Quality within constraints**: Responses don't just technically satisfy constraints; they produce good outputs within the constraints. A 3-bullet product description should actually be a good product description.
+
+**4. Exclusion constraints strictly followed**: "Do not use the word X" constraints are taken literally — the excluded words do not appear anywhere in the response.
+
+**5. Numeric constraints precise**: "Exactly 4 sentences" means 4, not 3 or 5. "Under 15 words" means the bullet must count to 14 or fewer.
+
+## Relationship to IFEval
+
+The IFEval benchmark (Zhou et al., 2023) measures instruction-following on prompts with verifiable constraints. The constraint types in this dataset directly correspond to IFEval's constraint categories:
+
+- Length constraints (word count, sentence count, paragraph count)
+- Format constraints (JSON, markdown, bullet lists)
+- Content constraints (keyword inclusion/exclusion)
+- Style constraints (language register, tone)
+
+Training on this dataset should improve scores on IFEval and similar instruction-following evaluations.
+
+## Use Cases
+
+- SFT fine-tuning for improved multi-constraint instruction following
+- Training data for models targeting IFEval benchmark improvement
+- Building AI writing assistants that reliably follow format specifications
+- Enterprise AI deployment where output format consistency is critical
+- Evaluation dataset development for constraint satisfaction testing
+- Complementary to `instruction-following-dpo-100k` (DPO pairs for same capability)
+
+## License
+
+Apache 2.0