Datasets:

PleIAs
/

data_samples

@@ -18,9 +18,9 @@ configs:
     path: personas/*.parquet
 ---
-## Multimodal Pretraining
-### Global academic thesis
 We hold the largest collection of academic thesis with more than three million documents in PDF at a global scale.
@@ -28,7 +28,7 @@ Our coverage extends significantly beyond western sources, with half of our hold
 The current sample include 1052 thesis in pdf formats in many languages.
-### Youtube-Commons
 Youtube-Commons is the current reference dataset for Youtube videos under creative commons allowing for full commercial reuse. The dataset was noticeably used to train Nvidia's SOTA text to speech model <a href="https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2">Parakeet</a>.
@@ -36,7 +36,7 @@ While the public version of Youtube-Commons only includes metadata and transcrip
 We provide an initial samples of 5,000 audio samples with associated metadata in parquet.
-### Non-US Patents
 We are currently collecting the largest available asset of non-US patents. It currently includes the complete collection of European patents (EPO) in the original pdf format and we're currently scaling our data collection to Asia.
@@ -44,7 +44,7 @@ Patents commonly come with technical diagrams we can communicate in a separate f
 The current sample includes 5,000 unique samples in large .tar files along with associated metadata.
-### Telecom
 In partnership with GSMA we collected Telco-Common Corpus, currently the largest dataset of telecom data.
@@ -52,7 +52,7 @@ Our internal asset includes the extent PDF and doc sources for multimodal traini
 The telecom corpus has been has been incorporated into the pretraining of Otel 2.0 by AT&T.
-### Global financial regulation
 In association with professional organizations in the finance sector in Europe, we have started to collect the largest global corpus of financial regulation and supervision, nearly one million documents in original PDF from central banks, market regulators and international standard-setters.
@@ -63,23 +63,23 @@ The collection is meant to support the creation of synthetic environments for st
 The current sample includes 5,000 documents in PDF, spanning every region, with associated metadata in parquet.
-## Synthetic data seeds/environment
-### Wikidata
 Seed-ready latest Wikidata dump at a statements/qualifier level. In contrast with the original dumps, our collection reconcile all ids to labels and restructure the nested statements into a flat structure easily retrievable as parquet.
 The sample is the first file in our collection of 2,369 parquet aggregations. Full dataset includes 600 millions statements and has been used extensively for synthetic environment grounding, diversification and search environment exercises (knowledge traversal, reconciliation). Through our partnership with Wikimedia Foundation, we maintain a regular update.
-### Global personas.
 Our internal assets scaling the synthetic personas at a global scale. We collected a unique corpus of representative first name and last names and aggregated many demographics distribution from international organizations and academic research.
 We provide a sample of 1 millions personas across 108 countries. Our full asset includes currently 100 millions personas but is indefinitely scalable. Similarly to Wikidata, we can also provide continuous updates taking into enhanced information and demographic changes.
-### Synthetic alignment
-### Synthetic social media
 We built a reusable synthetic pipeline for realistic social media simulations, with a specific focus on expression naturalness/intended noise that was presented this year at ACL

     path: personas/*.parquet
 ---
+# Multimodal Pretraining
+## Global academic thesis
 We hold the largest collection of academic thesis with more than three million documents in PDF at a global scale.
 The current sample include 1052 thesis in pdf formats in many languages.
+## Youtube-Commons
 Youtube-Commons is the current reference dataset for Youtube videos under creative commons allowing for full commercial reuse. The dataset was noticeably used to train Nvidia's SOTA text to speech model <a href="https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2">Parakeet</a>.
 We provide an initial samples of 5,000 audio samples with associated metadata in parquet.
+## Non-US Patents
 We are currently collecting the largest available asset of non-US patents. It currently includes the complete collection of European patents (EPO) in the original pdf format and we're currently scaling our data collection to Asia.
 The current sample includes 5,000 unique samples in large .tar files along with associated metadata.
+## Telecom
 In partnership with GSMA we collected Telco-Common Corpus, currently the largest dataset of telecom data.
 The telecom corpus has been has been incorporated into the pretraining of Otel 2.0 by AT&T.
+## Global financial regulation
 In association with professional organizations in the finance sector in Europe, we have started to collect the largest global corpus of financial regulation and supervision, nearly one million documents in original PDF from central banks, market regulators and international standard-setters.
 The current sample includes 5,000 documents in PDF, spanning every region, with associated metadata in parquet.
+# Synthetic data seeds/environment
+## Wikidata
 Seed-ready latest Wikidata dump at a statements/qualifier level. In contrast with the original dumps, our collection reconcile all ids to labels and restructure the nested statements into a flat structure easily retrievable as parquet.
 The sample is the first file in our collection of 2,369 parquet aggregations. Full dataset includes 600 millions statements and has been used extensively for synthetic environment grounding, diversification and search environment exercises (knowledge traversal, reconciliation). Through our partnership with Wikimedia Foundation, we maintain a regular update.
+## Global personas.
 Our internal assets scaling the synthetic personas at a global scale. We collected a unique corpus of representative first name and last names and aggregated many demographics distribution from international organizations and academic research.
 We provide a sample of 1 millions personas across 108 countries. Our full asset includes currently 100 millions personas but is indefinitely scalable. Similarly to Wikidata, we can also provide continuous updates taking into enhanced information and demographic changes.
+## Synthetic alignment
+## Synthetic social media
 We built a reusable synthetic pipeline for realistic social media simulations, with a specific focus on expression naturalness/intended noise that was presented this year at ACL