Update README.md

README.md

@@ -1,5 +1,114 @@
 ---
 license: other
-license_name: quora-qp-terms
-license_link: LICENSE
+license_name: quora-qp-release-terms
+license_link: https://quoradata.quora.com/First-Quora-Dataset-Release-Question-Pairs
+pretty_name: Quora Question Pairs (2017 canonical release)
+task_categories:
+  - sentence-similarity
+  - text-classification
+language:
+  - en
+size_categories:
+  - 100K<n<1M
+tags:
+  - embeddings
+  - sentence-similarity
+  - paraphrase
+  - duplicate-questions
+  - quora
+  - qqp
+source_datasets:
+  - original
 ---
+
+# Quora Question Pairs — canonical 2017 release
+
+A verbatim mirror of [Quora's January 2017 Question Pairs release](https://quoradata.quora.com/First-Quora-Dataset-Release-Question-Pairs), packaged as a single tab-delimited file. No rows added, removed, or reordered relative to the upstream `quora_duplicate_questions.tsv` — only the hosting moved.
+
+Re-hosted under Heliosoph for ingestion-pipeline stability — Quora's original CDN at `qim.fs.quoracdn.net` has been intermittently unreachable since the Kaggle competition wrapped, and the file has no checksumed permanent URL upstream.
+
+Credit: Shankar Iyer, Nikhil Dandekar, and Kornél Csernai (Quora, 2017) — questions authored by Quora users.
+
+## Why a mirror?
+
+The original release URL (`qim.fs.quoracdn.net/quora_duplicate_questions.tsv`) is the single canonical source, but it has gone offline for weeks at a time in past years, and there's no published checksum to verify a recovered copy against. Pinning a HuggingFace revision gives ingestion pipelines a stable, reproducible handle: the same SHA fetches the same bytes forever.
+
+The file itself is unmodified — md5 / sha256 against the upstream copy (when it's online) will match exactly.
+
+## What this repo contains
+
+```
+quora_duplicate_questions.tsv     # 404,290 rows, ~55 MB, UTF-8, tab-delimited
+```
+
+One file, six columns, header row included:
+
+| Column | Type | Meaning |
+|---|---|---|
+| `id` | int | Row index (0-based). |
+| `qid1` | int | Stable id of `question1` in Quora's internal question table. |
+| `qid2` | int | Stable id of `question2`. |
+| `question1` | string | First question, original casing + punctuation. |
+| `question2` | string | Second question, original casing + punctuation. |
+| `is_duplicate` | int (0/1) | Human label: 1 if the pair asks the same thing, else 0. |
+
+The `qid1` / `qid2` columns let you build a question-level view by deduping — the corpus is ~537k distinct questions arranged into 404k pairs.
+
+## How to use
+
+Load with the `datasets` library:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("Heliosoph/Quora-Question-Pairs", split="train")
+print(ds[0])
+# {'id': 0, 'qid1': 1, 'qid2': 2,
+#  'question1': 'What is the step by step guide to invest in share market in india?',
+#  'question2': 'What is the step by step guide to invest in share market?',
+#  'is_duplicate': 0}
+```
+
+Or read the TSV directly with pandas:
+
+```python
+import pandas as pd
+
+df = pd.read_csv("quora_duplicate_questions.tsv", sep="\t")
+print(df.shape)  # (404290, 6)
+print(df["is_duplicate"].mean())  # ~0.369 — about 37% of pairs are duplicates
+```
+
+## Dataset specs
+
+| | Spec |
+|---|---|
+| Rows | 404,290 question pairs |
+| Distinct questions | ~537,000 |
+| Duplicate share | ~36.9% labelled `is_duplicate = 1` |
+| Encoding | UTF-8 |
+| Delimiter | Tab (`\t`) |
+| Quoting | Minimal — embedded tabs in question text are rare but present; standard CSV/TSV readers handle them with double-quote escaping |
+| File size | ~55 MB on disk |
+| Language | English |
+
+## When to pick Quora Question Pairs
+
+- **Sentence-embedding evaluation**: encode `question1` + `question2`, take cosine similarity of the L2-normalised vectors, threshold for a binary classifier, report accuracy / F1 against `is_duplicate`. This is the canonical paired-cosine evaluation that every English sentence embedder (MiniLM, BGE, Jina, E5, GTE) reports.
+- **Duplicate-detection training**: 404k labelled pairs is enough to fine-tune a small encoder end-to-end on a single GPU in hours.
+- **Paraphrase identification**: the label space (same question or not) is a clean two-class proxy for paraphrase / non-paraphrase.
+
+For larger-scale retrieval (millions of passages) reach for **MS MARCO** instead — Quora QP is purpose-built for pairwise similarity, not document retrieval.
+
+## Label notes
+
+The `is_duplicate` flag is human-annotated but not gold-standard: Quora's release post explicitly notes that some labels are noisy ("the ground-truth labels contain some amount of noise: they are not guaranteed to be perfect"). For benchmark numbers, report on the full corpus rather than a hand-cleaned subset to keep results comparable.
+
+## License
+
+**Non-standard research-use terms** from Quora's 2017 release. Allows research, experimentation, and unmodified redistribution with attribution back to Quora. Commercial deployment is not explicitly addressed in the original announcement and should be reviewed separately.
+
+The HuggingFace metadata tags this `other` because no SPDX identifier matches; the canonical terms are the [release announcement](https://quoradata.quora.com/First-Quora-Dataset-Release-Question-Pairs).
+
+- Release announcement: [First Quora Dataset Release: Question Pairs](https://quoradata.quora.com/First-Quora-Dataset-Release-Question-Pairs)
+- Kaggle competition (same data): [Quora Question Pairs](https://www.kaggle.com/competitions/quora-question-pairs)