Datasets:

mammut
/

mammut-corpus-venezuela

@@ -1,11 +1,15 @@
-# 1. How to use
 How to load this dataset directly with the datasets library:
 `>>> from datasets import load_dataset`
 `>>> dataset = load_dataset("mammut-corpus-venezuela")`
-# 2. Dataset Summary
 **mammut-corpus-venezuela** is a dataset for Spanish language modeling. This dataset comprises a large number of Venezuelan and Latin-American Spanish texts, manually selected and collected in 2021. The data was collected by a process of web scraping from different portals, downloading of Telegram group chats' history, and selecting of Venezuelan and Latin-American Spanish corpus available online. The texts come from Venezuelan Spanish speakers, subtitlers, journalists, politicians, doctors, writers, and online sellers. Social biases may be present, and a percentage of the texts may be fake or contain misleading or offensive language.
@@ -13,19 +17,19 @@ Each record in the dataset contains the author of the text (anonymized for conve
 The dataset counts with a train split and a test split.
-# 3. Supported Tasks and Leaderboards
 This dataset can be used for language modeling.
-# 4. Languages
 The dataset contains Venezuelan and Latin-American Spanish.
-# 5. Dataset Structure
 Dataset structure features.
-## 5.1 Data Instances
 An example from the dataset:
@@ -41,12 +45,12 @@ An example from the dataset:
 The average word token count are provided below:
-## 5.2 Total of tokens (no spelling marks)
 Train: 92,431,194.
 Test: 4,876,739 (in another file).
-## 5.3 Data Fields
 The data have several fields:
@@ -58,7 +62,7 @@ The data have several fields:
   TOKENS: number of tokens (excluding punctuation marks) of SENTENCE.
   TYPE: linguistic register of the text.
-## 5.4 Data Splits
 The mammut-corpus-venezuela dataset has 2 splits: train and test. Below are the statistics:
@@ -67,13 +71,13 @@ Number of Instances in Split.
 Train: 2,983,302.
 Test: 157,011.
-# 6. Dataset Creation
-## 6.1 Curation Rationale
 The purpose of the mammut-corpus-venezuela dataset is language modeling. It can be used for pre-training a model from scratch or for fine-tuning on another pre-trained model.
-## 6.2 Source Data
 **6.2.1 Initial Data Collection and Normalization**
@@ -89,7 +93,7 @@ Text sources: El Estímulo (website), cinco8 (website), csm-1990 (oral speaking
 The texts come from Venezuelan Spanish speakers, subtitlers, journalists, politicians, doctors, writers, and online sellers.
-# 6.3 Annotations
 **6.3.1 Annotation process**
@@ -99,40 +103,40 @@ At the moment the dataset does not contain any additional annotations.
 Not applicable.
-## 6.4 Personal and Sensitive Information
 The data is partially anonymized. Also, there are messages from Telegram selling chats, some percentage of these messages may be fake or contain misleading or offensive language.
-# 7. Considerations for Using the Data
-## 7.1 Social Impact of Dataset
 The purpose of this dataset is to help the development of language modeling models (pre-training or fine-tuning) in Venezuelan Spanish.
-## 7.2 Discussion of Biases
 Most of the content comes from political, economical and sociological opinion articles. Social biases may be present.
-## 7.3 Other Known Limitations
 (If applicable, description of the other limitations in the data.)
 Not applicable.
-# 8. Additional Information
-## 8.1 Dataset Curators
 The data was originally collected by Lino Urdaneta and Miguel Riveros from Mammut.io.
-## 8.2 Licensing Information
 Not applicable.
-## 8.3 Citation Information
 Not applicable.
-## 8.4 Contributions
 Not applicable.

+# mammut-corpus-venezuela
+HuggingFace Dataset
+## 1. How to use
 How to load this dataset directly with the datasets library:
 `>>> from datasets import load_dataset`
 `>>> dataset = load_dataset("mammut-corpus-venezuela")`
+## 2. Dataset Summary
 **mammut-corpus-venezuela** is a dataset for Spanish language modeling. This dataset comprises a large number of Venezuelan and Latin-American Spanish texts, manually selected and collected in 2021. The data was collected by a process of web scraping from different portals, downloading of Telegram group chats' history, and selecting of Venezuelan and Latin-American Spanish corpus available online. The texts come from Venezuelan Spanish speakers, subtitlers, journalists, politicians, doctors, writers, and online sellers. Social biases may be present, and a percentage of the texts may be fake or contain misleading or offensive language.
 The dataset counts with a train split and a test split.
+## 3. Supported Tasks and Leaderboards
 This dataset can be used for language modeling.
+## 4. Languages
 The dataset contains Venezuelan and Latin-American Spanish.
+## 5. Dataset Structure
 Dataset structure features.
+### 5.1 Data Instances
 An example from the dataset:
 The average word token count are provided below:
+### 5.2 Total of tokens (no spelling marks)
 Train: 92,431,194.
 Test: 4,876,739 (in another file).
+### 5.3 Data Fields
 The data have several fields:
   TOKENS: number of tokens (excluding punctuation marks) of SENTENCE.
   TYPE: linguistic register of the text.
+### 5.4 Data Splits
 The mammut-corpus-venezuela dataset has 2 splits: train and test. Below are the statistics:
 Train: 2,983,302.
 Test: 157,011.
+## 6. Dataset Creation
+### 6.1 Curation Rationale
 The purpose of the mammut-corpus-venezuela dataset is language modeling. It can be used for pre-training a model from scratch or for fine-tuning on another pre-trained model.
+### 6.2 Source Data
 **6.2.1 Initial Data Collection and Normalization**
 The texts come from Venezuelan Spanish speakers, subtitlers, journalists, politicians, doctors, writers, and online sellers.
+## 6.3 Annotations
 **6.3.1 Annotation process**
 Not applicable.
+### 6.4 Personal and Sensitive Information
 The data is partially anonymized. Also, there are messages from Telegram selling chats, some percentage of these messages may be fake or contain misleading or offensive language.
+## 7. Considerations for Using the Data
+### 7.1 Social Impact of Dataset
 The purpose of this dataset is to help the development of language modeling models (pre-training or fine-tuning) in Venezuelan Spanish.
+### 7.2 Discussion of Biases
 Most of the content comes from political, economical and sociological opinion articles. Social biases may be present.
+### 7.3 Other Known Limitations
 (If applicable, description of the other limitations in the data.)
 Not applicable.
+## 8. Additional Information
+### 8.1 Dataset Curators
 The data was originally collected by Lino Urdaneta and Miguel Riveros from Mammut.io.
+### 8.2 Licensing Information
 Not applicable.
+### 8.3 Citation Information
 Not applicable.
+### 8.4 Contributions
 Not applicable.