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64
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YAML Metadata Warning: The task_categories "sentiment-classification" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, other

Telugu Colloquial Corpus (Tokenized)

This dataset is a tokenized version of the Telugu Colloquial Corpus (TeCC). It contains examples of informal, everyday Telugu language, including slang, regional variations, and conversational patterns.

Dataset Details

  • Language: Telugu (te)
  • Tokenization: Tokenized using the bert-base-multilingual-cased tokenizer from the transformers library.
  • Source: [Describe where the original data came from – e.g., collected from online forums, friends, family, manually transcribed conversations. Be as specific as possible.]
  • Purpose: This dataset is intended for use in NLP tasks such as:
    • Training language models for Telugu to generate text.
    • Fine-tuning pre-trained models for Telugu to improve understanding of informal language.
    • Developing chatbots and other conversational AI applications for Telugu.
    • Research on Telugu colloquial language.

Data Fields

The dataset contains the following features:

  • input_ids: The input token IDs (integers representing tokens in the tokenizer's vocabulary).
  • attention_mask: The attention mask (1 = attend to, 0 = ignore padding).
  • token_type_ids: Identifies which sequence a token belongs to (all 0s in this dataset, as it's a single-sequence task).

Data Collection and Preprocessing

The original data was collected from [Describe sources and methods used to collect the data]. It was then preprocessed as follows:

  • Tokenized using the bert-base-multilingual-cased tokenizer with these settings:
    • padding: longest
    • truncation: True
  • The following columns from the original JSON data were removed:
    • Colloquial_Telugu
    • Standard_Telugu
    • English
    • Source
    • Notes
    • Type
    • Answer
    • Meaning
    • Author

[Optional: Describe any other cleaning, normalization, or data augmentation steps you performed.]

Ethical Considerations

[Discuss any ethical considerations related to the data, such as privacy, bias, cultural sensitivity, or potential misuse. Be transparent about any potential limitations of the dataset.]

Limitations

  • The dataset is relatively small (304 examples), which may limit the performance of models trained on it.
  • The dataset may contain biases present in the original data sources.
  • The coverage of different Telugu dialects and social groups may be uneven.
  • The bert-base-multilingual-cased tokenizer may not be ideal for Telugu. A tokenizer trained specifically on Telugu text could improve results.

Citation

Please cite this dataset as follows:

#contact Ankitha Chowdary [email protected]

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