| --- |
| license: other |
| license_name: optitransfer-commercial |
| license_link: https://optitransfer.ch/terms |
| language: |
| - de |
| - fr |
| - en |
| - it |
| - pt |
| - es |
| - multilingual |
| tags: |
| - switzerland |
| - web-crawl |
| - common-crawl |
| - rag |
| - llm-training |
| - nlp |
| - multilingual |
| - german |
| - french |
| - swiss-data |
| - eu-ai-act |
| - sovereign-data |
| - pii-redacted |
| - quality-scored |
| - curated |
| - text-corpus |
| - web-corpus |
| - pre-training |
| - fine-tuning |
| - sft |
| - rag-ready |
| - data-provenance |
| - croissant |
| - italian |
| - english |
| - european |
| - europe |
| - common-crawl-derived |
| - high-quality |
| - deduplicated |
| - training-data |
| - instruction-tuning |
| - dpo |
| - language-model |
| - gpt |
| - llama |
| - mistral |
| - benchmark |
| - evaluation |
| - content-moderation |
| - swiss-german |
| - romansh |
| - alpine |
| - data-sovereignty |
| - gdpr |
| - compliance |
| - enterprise |
| - commercial |
| - production-ready |
| - cleaned |
| - filtered |
| - scored |
| - apertus |
| - swissbert |
| - euroai |
| - retrieval-augmented-generation |
| - knowledge-base |
| - text-mining |
| - information-extraction |
| - sentiment-analysis |
| - named-entity-recognition |
| - topic-modeling |
| - document-classification |
| size_categories: |
| - "100K<n<1M" |
| task_categories: |
| - text-generation |
| - feature-extraction |
| - text-classification |
| - question-answering |
| - summarization |
| - translation |
| pretty_name: "*.ch Swiss Web Premium (A+)" |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-00000-of-00001.parquet |
| dataset_info: |
| - config_name: default |
| features: |
| - name: url |
| dtype: string |
| - name: text |
| dtype: string |
| - name: language |
| dtype: string |
| - name: language_confidence |
| dtype: float64 |
| - name: quality_score |
| dtype: int64 |
| - name: quality_components_capitalization |
| dtype: int64 |
| - name: quality_components_digit_ratio |
| dtype: int64 |
| - name: quality_components_language_confidence |
| dtype: int64 |
| - name: quality_components_length |
| dtype: int64 |
| - name: quality_components_paragraphs |
| dtype: int64 |
| - name: quality_components_punctuation |
| dtype: int64 |
| - name: quality_components_repetition |
| dtype: int64 |
| - name: quality_components_sentence_structure |
| dtype: int64 |
| - name: quality_components_whitespace |
| dtype: int64 |
| - name: token_count |
| dtype: int64 |
| - name: word_count |
| dtype: int64 |
| - name: sentence_count |
| dtype: int64 |
| - name: perplexity |
| dtype: float64 |
| - name: repetition_line_repeat_ratio |
| dtype: float64 |
| - name: repetition_ngram_repeat_ratio |
| dtype: float64 |
| - name: repetition_word_repeat_ratio |
| dtype: float64 |
| - name: text_length |
| dtype: int64 |
| - name: paragraph_count |
| dtype: int64 |
| - name: avg_sentence_length |
| dtype: float64 |
| - name: domain |
| dtype: string |
| - name: tld |
| dtype: string |
| - name: url_path |
| dtype: string |
| - name: content_category |
| dtype: string |
| - name: category_info_alternative_categories |
| dtype: string |
| - name: category_info_category_confidence |
| dtype: float64 |
| - name: category_info_classification_method |
| dtype: string |
| - name: category_info_primary_category |
| dtype: string |
| - name: category_info_structural_features_avg_paragraph_length |
| dtype: float64 |
| - name: category_info_structural_features_has_code_blocks |
| dtype: bool |
| - name: category_info_structural_features_has_tables |
| dtype: bool |
| - name: category_info_structural_features_heading_count |
| dtype: int64 |
| - name: category_info_structural_features_word_count |
| dtype: int64 |
| - name: trust_tier |
| dtype: string |
| - name: trust_info_match_method |
| dtype: string |
| - name: trust_info_trust_score |
| dtype: float64 |
| - name: trust_info_trust_tier |
| dtype: string |
| - name: trust_info_components_domain_authority |
| dtype: float64 |
| - name: trust_info_components_freshness_signal |
| dtype: float64 |
| - name: trust_info_components_institutional_signal |
| dtype: float64 |
| - name: trust_info_components_spam_risk |
| dtype: float64 |
| - name: trust_info_components_ssl_signal |
| dtype: float64 |
| - name: timestamp |
| dtype: string |
| - name: crawl_date |
| dtype: string |
| - name: warc_source_key |
| dtype: string |
| - name: mime |
| dtype: string |
| - name: status |
| dtype: string |
| - name: digest |
| dtype: string |
| - name: filename |
| dtype: string |
| - name: offset |
| dtype: string |
| - name: length |
| dtype: string |
| - name: pii_detected |
| dtype: string |
| - name: pii_redacted_count |
| dtype: int64 |
| - name: code_language |
| dtype: string |
| - name: code_confidence |
| dtype: float64 |
| - name: academic_abstract |
| dtype: string |
| - name: academic_arxiv_id |
| dtype: float64 |
| - name: academic_authors |
| dtype: string |
| - name: academic_categories |
| dtype: string |
| - name: academic_doi |
| dtype: string |
| - name: academic_is_academic |
| dtype: bool |
| - name: academic_title |
| dtype: float64 |
| - name: academic_year |
| dtype: float64 |
| - name: news_category |
| dtype: float64 |
| - name: news_headline |
| dtype: string |
| - name: news_is_news |
| dtype: bool |
| - name: news_publish_date |
| dtype: string |
| - name: news_source |
| dtype: string |
| - name: slop_score |
| dtype: float64 |
| - name: spatial_awareness |
| dtype: bool |
| - name: persuasion_audience |
| dtype: string |
| - name: skill_tags |
| dtype: string |
| - name: instruction_style |
| dtype: string |
| - name: difficulty_level |
| dtype: string |
| splits: |
| - name: train |
| num_examples: 10000 |
| gated: manual |
| extra_gated_prompt: >- |
| This dataset is a curated, production-grade Swiss web corpus from OptiTransfer. |
| The sample (10,000 records) is available upon approval for evaluation. |
| The full dataset (110,491 records across 22 production files including Parquet, JSONL, |
| language splits, and RAG chunks) is available under commercial licence -- delivered |
| instantly via HuggingFace upon payment settlement (bank transfer, TWINT, or crypto). |
| Contact data@optitransfer.ch for pricing. |
| Please complete all fields to request access. |
| extra_gated_fields: |
| Full name: text |
| Company / Organisation: text |
| Job title: text |
| Country: country |
| Business email: text |
| Intended use: |
| type: select |
| options: |
| - LLM pre-training |
| - LLM fine-tuning |
| - RAG pipeline |
| - Research / Academic |
| - Evaluation / Benchmarking |
| - Multilingual NLP |
| - Other |
| Budget range: |
| type: select |
| options: |
| - Evaluating (no budget yet) |
| - Under $1,000 |
| - $1,000 - $5,000 |
| - $5,000 - $25,000 |
| - $25,000+ |
| - Enterprise / custom |
| I agree to the OptiTransfer Terms of Service: checkbox |
| extra_gated_button_content: "Request Access" |
| --- |
| |
| # *.ch Swiss Web Premium (A+) |
| |
| **Grade A+ -- 112.4M tokens -- 110,491 records -- 29 languages -- Full provenance -- PII-redacted -- RAG-ready -- SFT-formatted** |
| |
| > A production-grade Swiss web corpus from the `.ch` TLD namespace. 110,491 documents independently quality-scored (avg 93.3/100, minimum 90), PII-redacted, and SHA256-verified. Built for LLM training, RAG pipelines, SFT fine-tuning, and multilingual NLP. |
| |
| --- |
| |
| ## OptiTransferData Portfolio |
| |
| > Premium sovereign web corpora for LLM training, RAG pipelines, and multilingual NLP. EU AI Act compliant, PII-redacted, SHA256-verified. |
| |
| | Dataset | Records | Type | Repositories | |
| |---|---|---|---| |
| | *.ch Swiss Web Premium (A+) | 110,491 docs, 78 fields | Web corpus + SFT + RAG | [Sample / Storefront](https://huggingface.co/datasets/OptiTransferData/swiss-web-premium-ch) -- [Full Dataset](https://huggingface.co/datasets/OptiTransferData/swiss-web-premium-ch-full) | |
|
|
| Contact [data@optitransfer.ch](mailto:data@optitransfer.ch) to discuss your data requirements or get notified when new datasets launch. |
|
|
| --- |
|
|
| ## Dataset Summary |
|
|
| | Property | Value | |
| |---|---| |
| | **Product Name** | *.ch Swiss Web Premium (A+) | |
| | **Dataset ID** | cache_ch_ac906c8b | |
| | **Total Records** | 110,491 unique source URLs | |
| | **Total Tokens** | 112,428,245 (tiktoken cl100k_base / GPT-4) | |
| | **Total Characters** | 367.5M | |
| | **Total Words** | 51,785,182 | |
| | **Quality Grade** | A+ (avg 93.3/100, floor 90, ceiling 96) | |
| | **Languages** | 29 (67.1% German, 20.0% French, 7.9% English, 4.4% Italian + 25 more) | |
| | **Content Categories** | 13 (general, news, ecommerce, documentation, academic, legal, education, government, discussion, finance, encyclopedia, code, blog) | |
| | **Unique Domains** | 19,927 (domain cap: 500 records per domain) | |
| | **Crawl Source** | Common Crawl CC-MAIN-2026-12 | |
| | **Crawl Window** | 2013-05-18 to 2026-03-17 | |
| | **Total Size** | 554.1 MB (all formats combined) | |
| | **RAG Chunks** | 196,304 pre-built (512-token windows, 64-token overlap) | |
| | **Provenance** | Full WARC-level audit trail (filename, offset, digest) | |
| | **Compliance** | EU AI Act, FADP-aligned, Swiss-hosted processing | |
| | **Slop Score** | 0.001 mean (99.9% human-authored content) | |
| | **Pipeline** | OptiTransfer Tier 6 Sidecar sprint_20_v6 | |
| | **Certificate** | OT-CERT-CACHE_CH | |
| | **QA Report** | 43-page v6 PDF (full enumeration, cross-validation, provenance) | |
| |
| --- |
| |
| ## What Is in This Repository |
| |
| ### Evaluation Sample (10,000 records -- available on approval) |
| |
| - `data/train-00000-of-00001.parquet` -- Stratified sample preserving language, category, and quality distribution (directly loadable via HuggingFace Datasets library) |
| - `docs/schema.json` -- Full JSON Schema for all 78 fields |
| - `docs/data_card.md` -- Detailed methodology and quality documentation |
| - `docs/manifest.json` -- Complete dataset statistics and pipeline configuration |
| - `docs/quality_certificate.html` -- Visual quality certificate |
| - `docs/domain_breakdown.csv` -- All 19,927 domains with record counts |
| - `docs/skill_distribution.csv` -- ML skill tag and difficulty distributions |
| - `docs/sample.csv` -- Tabular sample summary |
| - `docs/SHA256SUMS` -- SHA256 checksums for all 22 production files |
| - `reports/OptiTransfer_QA_Report_v6_cache_ch_ac906c8b.pdf` -- 43-page QA report (v6) |
| |
| ### Full Dataset (available under commercial licence) |
| |
| The full dataset is available at [OptiTransferData/swiss-web-premium-ch-full](https://huggingface.co/datasets/OptiTransferData/swiss-web-premium-ch-full): |
| |
| - 7x Parquet shards (140.3 MB, zstd compressed) -- optimal for Spark, Arrow, BigQuery |
| - 7x JSONL.gz shards (147.0 MB compressed) -- universal compatibility |
| - 4x Language splits: DE (95.4 MB), FR (28.1 MB), EN (10.3 MB), IT (5.3 MB) |
| - 4x RAG chunk shards (127.7 MB) -- 196,304 retrieval-ready chunks |
| - SHA256SUMS for all 22 production files |
| - Full 43-page QA report (v6) |
| |
| Contact [data@optitransfer.ch](mailto:data@optitransfer.ch) for full dataset pricing and licensing. |
| |
| --- |
| |
| ## Quality Scoring Methodology |
| |
| Every document is evaluated using a 9-component weighted quality algorithm. Only records scoring 90/100 or above are included in this A+ build. |
| |
| ### Quality Score Distribution |
| |
| | Score | Records | Percentage | |
| |---|---|---| |
| | 96 | 26,266 | 23.8% | |
| | 95 | 15,365 | 13.9% | |
| | 94 | 6,239 | 5.6% | |
| | 93 | 20,401 | 18.5% | |
| | 92 | 14,603 | 13.2% | |
| | 91 | 15,089 | 13.7% | |
| | 90 | 12,528 | 11.3% | |
| |
| ### Quality Component Means |
| |
| | Component | Mean Score | What It Measures | |
| |---|---|---| |
| | whitespace | 99.95 | Normalisation and formatting consistency | |
| | digit_ratio | 99.02 | Numeric-to-alphabetic character balance | |
| | repetition | 98.44 | Absence of boilerplate or repetitive passages | |
| | capitalization | 98.25 | Correct and consistent capitalisation | |
| | length | 97.31 | Document length relative to optimal range | |
| | language_confidence | 97.09 | FastText detection confidence | |
| | sentence_structure | 96.87 | Grammatical completeness and variety | |
| | punctuation | 93.47 | Punctuation density and correctness | |
| | paragraphs | 49.51 | Paragraph count and structural depth | |
| |
| --- |
| |
| ## Language Distribution |
| |
| | Language | Records | Percentage | Dedicated Split | |
| |---|---|---|---| |
| | German (de) | 74,130 | 67.1% | Yes | |
| | French (fr) | 22,072 | 20.0% | Yes | |
| | English (en) | 8,695 | 7.9% | Yes | |
| | Italian (it) | 4,823 | 4.4% | Yes | |
| | Portuguese (pt) | 187 | 0.2% | -- | |
| | Spanish (es) | 164 | 0.1% | -- | |
| | Russian (ru) | 98 | 0.1% | -- | |
| | Tamil (ta) | 68 | 0.1% | -- | |
| | + 21 more | 254 | 0.2% | -- | |
| |
| All records originate from `.ch` TLD domains. Language distribution reflects the multilingual nature of Switzerland's web presence, with all four national languages represented. |
| |
| --- |
| |
| ## Record Schema (78 fields) |
| |
| Each record contains rich metadata for maximum ML utility. |
| |
| ### Core Fields |
| |
| | Field | Type | Description | |
| |---|---|---| |
| | `url` | string | Source URL (unique, deduplicated) | |
| | `text` | string | Clean extracted text (PII redacted where detected) | |
| | `language` | string | ISO 639-1 language code (FastText lid.176) | |
| | `language_confidence` | float | Detection confidence (0-1) | |
| | `quality_score` | int | 9-component quality score (90-96 in this build) | |
| | `quality_components` | object | Individual scores: length, sentence_structure, paragraphs, capitalization, punctuation, digit_ratio, whitespace, repetition, language_confidence | |
| | `token_count` | int | GPT-4 token count (tiktoken cl100k_base) | |
| | `word_count` | int | Word count | |
| | `sentence_count` | int | Sentence count | |
| | `perplexity` | float | Character-level entropy (mean 3.02, IQR 0.14) | |
| | `text_length` | int | Character count | |
| | `paragraph_count` | int | Number of paragraphs | |
| | `avg_sentence_length` | float | Mean sentence length in words | |
| |
| ### Classification and Trust |
| |
| | Field | Type | Description | |
| |---|---|---| |
| | `content_category` | string | One of: general, news, ecommerce, documentation, academic, legal, education, government, discussion, finance, encyclopedia, code, blog | |
| | `category_info` | object | Semantic categorisation with confidence score and structural features | |
| | `trust_tier` | string | Domain trust level: established (70.4%), general (24.9%), news_editorial (1.9%), academic (1.7%), institutional (1.1%) | |
| | `trust_info` | object | Multi-factor trust scoring with component breakdown | |
| | `domain` | string | Source domain | |
| | `tld` | string | Top-level domain (always `ch`) | |
| | `url_path` | string | URL path component | |
| |
| ### ML-Ready Enrichments |
| |
| | Field | Type | Description | |
| |---|---|---| |
| | `skill_tags` | array | 31 distinct skill families with sub-variants (e.g., `reasoning_arithmetic`, `coding_function_calling`, `creative_writing_fiction`) | |
| | `instruction_style` | string | One of: `detailed` (65.1%), `brief` (31.2%), `json_structured` (1.3%), `step-by-step` (1.1%), `conversational` (1.0%), `formal` (0.2%) | |
| | `difficulty_level` | string | `intermediate` (70.7%) or `expert` (29.3%) | |
| | `slop_score` | float | AI-generated text marker (0 = clean human, 1 = heavy slop). Mean: 0.001 | |
| | `spatial_awareness` | bool | Whether text contains meaningful spatial/positional descriptions (2.4% of records) | |
| | `persuasion_audience` | string or null | Target audience when persuasive content detected: `commercial`, `public`, `academic`, `institutional` | |
| |
| ### Provenance and Compliance |
| |
| | Field | Type | Description | |
| |---|---|---| |
| | `timestamp` | string | Original crawl timestamp (ISO 8601) | |
| | `crawl_date` | string | Crawl date | |
| | `warc_source_key` | string | WARC source key | |
| | `mime` | string | MIME type from WARC header | |
| | `status` | string | HTTP status code | |
| | `digest` | string | SHA1 content digest from WARC | |
| | `filename` | string | Source WARC filename (enables source reconstruction) | |
| | `offset` | string | Byte offset in WARC | |
| | `length` | string | Record length in WARC | |
| |
| ### Safety and PII |
| |
| | Field | Type | Description | |
| |---|---|---| |
| | `pii_detected` | array | PII types found: email, phone_intl, phone_swiss, credit_card, iban, ahv_swiss, ssn_us | |
| | `pii_redacted_count` | int | Number of token-level [REDACTED] replacements applied | |
| | `repetition` | object | Word repeat ratio, n-gram repeat ratio, line repeat ratio | |
| |
| ### Content-Specific (populated when applicable) |
| |
| | Field | Type | Description | |
| |---|---|---| |
| | `code_language` | string or null | Programming language (SQL, Python, JavaScript, etc.) | |
| | `code_confidence` | float or null | Code detection confidence | |
| | `academic` | object or null | arXiv ID, DOI, abstract, categories | |
| | `news` | object or null | Headline, publish date, source, category | |
| |
| --- |
| |
| ## Token and Perplexity Statistics |
| |
| ### Token Distribution |
| |
| | Range | Records | Percentage | ML Use Case | |
| |---|---|---|---| |
| | 0-100 | 651 | 0.6% | Short texts, classification training | |
| | 100-500 | 39,760 | 36.0% | SFT / RLHF examples, RAG chunks | |
| | 500-1,000 | 33,072 | 29.9% | Continued pre-training, summarisation | |
| | 1,000-2,000 | 24,368 | 22.1% | Long-form SFT, document understanding | |
| | 2,000-5,000 | 11,159 | 10.1% | Extended context, legal/encyclopedia | |
| | 5,000+ | 1,481 | 1.3% | Long-context models | |
| |
| **Stats:** Mean 1,018 tokens/doc -- Median 680 -- Min 30 -- Max 17,200 |
| |
| ### Perplexity |
| |
| | Metric | Value | |
| |---|---| |
| | Mean | 3.02 | |
| | Median | 3.01 | |
| | IQR | 0.14 (2.94-3.08) | |
| | Min-Max | 1.10-5.08 | |
| |
| The tight IQR of 0.14 confirms consistent text quality across the entire corpus. |
| |
| --- |
| |
| ## PII and Safety |
| |
| All records have been processed through OptiTransfer's PII detection and redaction pipeline: |
| |
| | Metric | Value | |
| |---|---| |
| | Records with PII detected | 33,803 (30.6%) | |
| | Total redactions applied | 88,643 | |
| | PII types detected | Email, phone (international), phone (Swiss), credit card, IBAN, AHV (Swiss), SSN (US) | |
| | Compliance | GDPR-aligned, FADP-aligned, EU AI Act | |
| |
| All detected PII instances have been replaced with `[REDACTED]` tokens prior to dataset publication. |
| |
| --- |
| |
| ## Content Categories |
| |
| | Category | Records | Percentage | |
| |---|---|---| |
| | general | 72,752 | 65.8% | |
| | news | 21,263 | 19.2% | |
| | ecommerce | 8,112 | 7.3% | |
| | documentation | 3,340 | 3.0% | |
| | academic | 1,157 | 1.0% | |
| | legal | 1,093 | 1.0% | |
| | education | 919 | 0.8% | |
| | government | 834 | 0.8% | |
| | discussion | 596 | 0.5% | |
| | finance | 248 | 0.2% | |
| | encyclopedia | 99 | 0.1% | |
| | code | 77 | 0.1% | |
| |
| --- |
| |
| ## Processing Pipeline |
| |
| ``` |
| 1. WARC Extraction Raw extraction from Common Crawl (CC-MAIN-2026-12) |
| 2. Swiss Transfer Zero-copy AWS S3 to Exoscale SOS (Zurich, Switzerland) |
| 3. Text Extraction Trafilatura HTML extraction (boilerplate removal) |
| 4. Language Detection FastText lid.176 (176 languages) |
| 5. Quality Scoring 9-component weighted scoring (0-100 scale) |
| 6. Tokenization tiktoken cl100k_base (GPT-4 compatible) |
| 7. Classification Content categorisation + multi-factor trust scoring |
| 8. Metadata Extract Code detection (15 languages), academic, news metadata |
| 9. PII Redaction Email, phone, IBAN, credit card, AHV/SSN patterns |
| 10. Domain Gate Denylist filtering for known problematic domains |
| 11. Deduplication SHA1 content digest dedup + URL dedup |
| 12. Quality Filter Minimum quality score: 90 |
| 13. Output Generation JSONL.gz sharded + Parquet (zstd) + RAG chunks + language splits |
| ``` |
| |
| **Filtering summary:** 354,964 source records -> 110,491 delivered (31.1% pass rate) |
| |
| | Stage | Records Removed | |
| |---|---| |
| | Quality filter | 217,771 | |
| | Deduplication | 15,441 | |
| | Domain cap (500/domain) | 10,661 | |
| | Low trust | 94 | |
| | Premium gate | 82 | |
| | URL dedup | 125 | |
| |
| --- |
| |
| ## Quick Start |
| |
| ### Load the Sample with HuggingFace Datasets |
| |
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("OptiTransferData/swiss-web-premium-ch") |
| print(ds["train"][0]) |
| ``` |
| |
| ### Filter by Quality and Language |
| |
| ```python |
| # Load and filter for high-quality German records |
| ds = load_dataset("OptiTransferData/swiss-web-premium-ch") |
| df = ds["train"].to_pandas() |
| |
| high_quality_de = df[(df.quality_score >= 95) & (df.language == "de")] |
| print(f"{len(high_quality_de)} premium German records") |
| ``` |
| |
| ### Load Full Dataset from Parquet (licensed customers) |
| |
| ```python |
| import pandas as pd |
| |
| # Load all 7 shards |
| dfs = [pd.read_parquet(f"cache_ch_ac906c8b_{i:03d}.parquet") for i in range(1, 8)] |
| df = pd.concat(dfs, ignore_index=True) |
| print(f"{len(df)} records, {df.token_count.sum():,} tokens") |
| ``` |
| |
| ### Load Full Dataset via HuggingFace Datasets (licensed customers) |
| |
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("OptiTransferData/swiss-web-premium-ch-full") |
| print(f"{len(ds['train'])} records") |
| print(ds["train"][0]) |
| ``` |
| |
| ### Load from JSONL |
| |
| ```python |
| import gzip, json |
| |
| with gzip.open("cache_ch_ac906c8b_001.jsonl.gz", "rt") as f: |
| for line in f: |
| record = json.loads(line) |
| print(record["url"], record["quality_score"], record["token_count"]) |
| ``` |
| |
| ### Use Language Splits |
| |
| ```python |
| import gzip, json |
| |
| # Load only French records |
| with gzip.open("cache_ch_ac906c8b_fr.jsonl.gz", "rt") as f: |
| fr_records = [json.loads(line) for line in f] |
| print(f"{len(fr_records)} French records") |
| ``` |
| |
| ### Use RAG Chunks |
| |
| ```python |
| import gzip, json |
| |
| with gzip.open("cache_ch_ac906c8b_rag_001.jsonl.gz", "rt") as f: |
| chunks = [json.loads(line) for line in f] |
| print(f"{len(chunks)} RAG chunks (512-token, 64-overlap)") |
| ``` |
| |
| --- |
| |
| ## Pricing and Access |
| |
| | Tier | Contents | Availability | |
| |---|---|---| |
| | **Sample** | 10,000 records (this repository) | Free -- request access above | |
| | **Full Dataset** | 110,491 records + Parquet + JSONL + 4 language splits + RAG chunks (22 files) | Commercial licence | |
| | **Enterprise** | Multi-TLD packs, custom pipelines, priority support | Custom pricing | |
| |
| ### How to Purchase the Full Dataset |
| |
| 1. **Evaluate** -- Request access above and explore the 10,000-record sample |
| 2. **Contact us** -- Email [data@optitransfer.ch](mailto:data@optitransfer.ch) to discuss licensing and receive a quote |
| 3. **Settle payment** -- We accept the following payment methods: |
| |
| | Method | Details | |
| |---|---| |
| | **Bank Transfer (SEPA / SWIFT)** | Invoice provided with full banking details upon agreement | |
| | **TWINT** | Swiss instant payment -- settle directly via TWINT (details provided on invoice) | |
| | **Crypto (BTC / ETH / SOL)** | Wallet addresses provided on request -- contact us for details | |
| |
| 4. **Instant delivery** -- Upon payment confirmation, you receive access to the full dataset on HuggingFace within 24 hours. All 22 production files (Parquet, JSONL, language splits, RAG chunks) delivered through HuggingFace secure infrastructure. |
| |
| Enterprise and volume buyers: Custom invoicing, purchase orders, and multi-dataset bundles available. Contact us for tailored terms. |
| |
| [data@optitransfer.ch](mailto:data@optitransfer.ch) -- [optitransfer.ch](https://optitransfer.ch) |
| |
| > OptiTransfer delivers sovereign, compliance-ready web corpora for AI teams building in regulated markets. Every dataset ships with full provenance, SHA256 verification, and Swiss-hosted processing. |
| |
| --- |
| |
| ## Quality Assurance |
| |
| This dataset is accompanied by a comprehensive 43-page QA report (v6) containing: |
| |
| - Full enumeration of all 110,491 records |
| - Cross-validation across all supporting documents (10/11 pass, 1 finding within tolerance) |
| - Language distribution analysis (29 languages) |
| - Quality component breakdown (9-axis scoring) |
| - Domain diversity analysis (19,927 unique domains) |
| - PII detection and redaction audit (88,643 redactions) |
| - Temporal coverage analysis (13-year span: 2013-2026) |
| - Slop score analysis (AI content detection) |
| - RAG suitability assessment (196,304 chunks) |
| - Data provenance and traceability chain |
| - Regulatory compliance statement (EU AI Act, FADP) |
| |
| The report is available at `reports/OptiTransfer_QA_Report_v6_cache_ch_ac906c8b.pdf` in both the sample and full repositories. |
| |
| --- |
| |
| ## Licence and Attribution |
| |
| - **Source data:** Common Crawl Foundation Terms of Use ([commoncrawl.org/terms-of-use](https://commoncrawl.org/terms-of-use)) |
| - **Processing and packaging:** OptiTransfer.ch proprietary pipeline (Tier 6 Sidecar sprint_20_v6) |
| - **Redistribution:** Subject to OptiTransfer.ch [Terms of Service](https://optitransfer.ch/terms) |
| - **Important:** Page content may be copyrighted by original authors; use subject to applicable copyright laws. |
| |
| ## Citation |
| |
| ```bibtex |
| @dataset{optitransfer_ch_2026, |
| title = {*.ch Swiss Web Premium (A+)}, |
| author = {OptiTransfer}, |
| year = {2026}, |
| url = {https://huggingface.co/datasets/OptiTransferData/swiss-web-premium-ch}, |
| note = {110,491 records, 112.4M tokens, Grade A+, .ch TLD, EU AI Act-aligned} |
| } |
| ``` |
| |
| --- |
| |
| *Product ID: `cache_ch_ac906c8b` -- Source: CC-MAIN-2026-12 -- Generated: 2026-03-24 -- Pipeline: OptiTransfer.ch Tier 6 Sidecar sprint_20_v6 -- Certificate: OT-CERT-CACHE_CH* |
| |
