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dataset_infos.json

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+{"din0s--ccmatrix_en-it_lrs_backtranslated": {
+    "description": "CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB\n\nWe show that margin-based bitext mining in LASER's multilingual sentence space can be applied to\nmonolingual corpora of billions of sentences to produce high quality aligned translation data.\nWe use thirty-two snapshots of a curated common crawl corpus [1] totaling 69 billion unique sentences.\nUsing one unified approach for 80 languages, we were able to mine 10.8 billion parallel sentences,\nout of which only 2.9 billion are aligned with English.\n\nIMPORTANT: Please cite reference [2][3] if you use this data.\n\n[1] Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzm\u00e1n, Armand Jouli\n    and Edouard Grave, CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data\n\n[2] Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Edouard Grave and Armand Joulin,\n    CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB\n\n[3] Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines,\n    Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, Naman Goyal, Tom Birch, Vitaliy Liptchinsky,\n    Sergey Edunov, Edouard Grave, Michael Auli, and Armand Joulin.\n    Beyond English-Centric Multilingual Machine Translation\n    \n90 languages, 1,197 bitexts\ntotal number of files: 90\ntotal number of tokens: 112.14G\ntotal number of sentence fragments: 7.37G\n\n\nCCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB\n\nWe show that margin-based bitext mining in LASER's multilingual sentence space can be applied to\nmonolingual corpora of billions of sentences to produce high quality aligned translation data.\nWe use thirty-two snapshots of a curated common crawl corpus [1] totaling 69 billion unique sentences.\nUsing one unified approach for 80 languages, we were able to mine 10.8 billion parallel sentences,\nout of which only 2.9 billion are aligned with English.\n\nIMPORTANT: Please cite reference [2][3] if you use this data.\n\n[1] Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzm\u00e1n, Armand Jouli\n    and Edouard Grave, CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data\n\n[2] Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Edouard Grave and Armand Joulin,\n    CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB\n\n[3] Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines,\n    Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, Naman Goyal, Tom Birch, Vitaliy Liptchinsky,\n    Sergey Edunov, Edouard Grave, Michael Auli, and Armand Joulin.\n    Beyond English-Centric Multilingual Machine Translation\n    \n90 languages, 1,197 bitexts\ntotal number of files: 90\ntotal number of tokens: 112.14G\ntotal number of sentence fragments: 7.37G",
+    "citation": "Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzm\u00e1n, Armand Jouli and Edouard Grave, CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data\n\n\nGuillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzm\u00e1n, Armand Jouli and Edouard Grave, CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data",
+    "homepage": "https://opus.nlpl.eu/CCMatrix.php",
+    "license": "",
+    "features": {
+        "id": {
+            "dtype": "int32",
+            "id": null,
+            "_type": "Value"
+        },
+        "score": {
+            "dtype": "float32",
+            "id": null,
+            "_type": "Value"
+        },
+        "translation": {
+            "languages": [
+                "en",
+                "it"
+            ],
+            "id": null,
+            "_type": "Translation"
+        }
+    },
+    "post_processed": null,
+    "supervised_keys": null,
+    "task_templates": null,
+    "builder_name": null,
+    "config_name": null,
+    "version": null,
+    "splits": {
+        "train": {
+            "name": "train",
+            "num_bytes": 9544615,
+            "num_examples": 39000,
+            "dataset_name": "ccmatrix_en-it_lrs_backtranslated"
+        }
+    },
+    "download_checksums": null,
+    "download_size": 6544910,
+    "post_processing_size": null,
+    "dataset_size": 9544615,
+    "size_in_bytes": 16089525
+}}