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  pretty_name: ROSTSC
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  ---
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-
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  # RO-STS-Corpus
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  ## Overview
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  | manual/generated | hand | 6471 |
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  | **Total** | | **70053** |
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  ## Usage
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  This dataset can be used for:
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  - Fine-tuning and evaluating sentence embedding models for Romanian.
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  - Research on semantic textual similarity and natural language understanding (NLU) in Romanian.
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  ## License
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- This dataset is licensed under the **Apache 2.0 License**.
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  ## Citation
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  If you use RO-STS-Corpus in your research, please cite this dataset as follows:
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  We acknowledge contributions from various resources used in compiling and annotating this dataset.
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  ---
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- Further details and additional metadata will be added in future versions.
 
 
 
 
 
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  pretty_name: ROSTSC
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  ---
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  # RO-STS-Corpus
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  ## Overview
 
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  | manual/generated | hand | 6471 |
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  | **Total** | | **70053** |
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+ ## Data Collection and Processing
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+ The data has been collected from existing datasets, primarily in English, and translated into Romanian. Some datasets were originally in Romanian and were used either in full or in part.
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+
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  ## Usage
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  This dataset can be used for:
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  - Fine-tuning and evaluating sentence embedding models for Romanian.
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  - Research on semantic textual similarity and natural language understanding (NLU) in Romanian.
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+ ### How to Load the Dataset
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+
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+ You can load the dataset using the `datasets` library from Hugging Face:
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+ ```python
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+ from datasets import load_dataset
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+
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+ dataset = load_dataset("RO-STS-Corpus")
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+
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+ # Access the train split
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+ train_data = dataset["train"]
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+
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+ # View an example
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+ print(train_data[0])
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+ ```
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+ Alternatively, if you have the dataset as a CSV file, you can load it using `pandas`:
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+ ```python
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+ import pandas as pd
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+ df = pd.read_csv("RO-STS-Corpus.csv")
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+ print(df.head())
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+ ```
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+ This allows you to easily integrate the dataset into your training or evaluation pipeline.
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+
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  ## License
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+ This dataset is licensed under **Apache 2.0**.
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  ## Citation
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  If you use RO-STS-Corpus in your research, please cite this dataset as follows:
 
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  We acknowledge contributions from various resources used in compiling and annotating this dataset.
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  ---
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+ Further details and additional metadata will be added in future versions.
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+