Update README.md

README.md

@@ -11,7 +11,7 @@ language:
 license: cc-by-2.0
 task_categories:
 - translation
-pretty_name: Tatoeba Translations Dataset
+pretty_name: Multilingual-to-Kabardian Tatoeba Translations Dataset
 size_categories:
 - 1M<n<10M
 tags:
@@ -122,7 +122,7 @@ Each instance in the dataset contains:
 {
     'source_tatoeba_id': 7627627,                 # Tatoeba sentence ID
     'source_lang': 'eng',                         # Source language code
-    'source_text': 'He\'s always happy.',          # Original text
+    'source_text': 'He\'s always happy.',         # Original text
     'target_text': 'Ар сыт щыгъуи насыпыфIэщ.',   # Translated text
     'similarity_score': 0.9283,                   # Translation similarity score
     'nllb_model_version': 'rus-kbd-v1.3.4'        # Model used for verification
@@ -134,7 +134,7 @@ Each instance in the dataset contains:
 - `source_tatoeba_id`: Unique identifier from Tatoeba
 - `source_lang`: Language code of the source text
 - `source_text`: Original text in source language
-- `target_text`: Translated text (predominantly in Russian)
+- `target_text`: Translated text
 - `similarity_score`: Similarity score between source and target texts
 - `nllb_model_version`: Version of the translation model used for verification
 
@@ -160,12 +160,12 @@ The source data comes from [Tatoeba](https://tatoeba.org/), a free collaborative
 1. Sentences were extracted from Tatoeba's database
 2. Filtered by language pairs
 3. Translated using various versions of NLLB-200-kbd model
-4. Translation quality was assessed using panagoa/LaBSE-kbd-v0.1 model to compute similarity scores
+4. Translation quality was assessed using [panagoa/LaBSE-kbd-v0.1](https://huggingface.co/panagoa/LaBSE-kbd-v0.1) model to compute similarity scores
 5. For quality assurance, translations were filtered using the 75th percentile of similarity scores for each language pair as a threshold
 
 ### Annotations
 
-The translations were generated using different versions of NLLB-200-kbd model. The similarity scores were computed using panagoa/LaBSE-kbd-v0.1 model to ensure translation quality and consistency.
+The translations were generated using different versions of NLLB-200-kbd model. The similarity scores were computed using [panagoa/LaBSE-kbd-v0.1](https://huggingface.co/panagoa/LaBSE-kbd-v0.1) model to ensure translation quality and consistency.
 
 ## Additional Information
 
@@ -180,12 +180,12 @@ This dataset is licensed under [Creative Commons Attribution 2.0](https://creati
 ### Citation Information
 
 ```bibtex
-@misc{tatoeba_translations_2024,
-    title={Multilingual Tatoeba Translations Dataset},
-    author={Your Name},
-    year={2024},
+@misc{tatoeba_translations_2025,
+    title={Multilingual-to-Kabardian Tatoeba Translations Dataset},
+    author={Adam Panagov},
+    year={2025},
     publisher={Hugging Face},
-    howpublished={\url{https://huggingface.co/datasets/username/dataset-name}}
+    howpublished={\url{https://huggingface.co/datasets/panagoa/tatoeba_kbd}}
 }
 ```
 
@@ -199,11 +199,11 @@ Thanks to [@Tatoeba](https://tatoeba.org/) for providing the source data.
 from datasets import load_dataset
 
 # Load the entire dataset
-dataset = load_dataset("username/dataset-name")
+dataset = load_dataset("panagoa/tatoeba_kbd")
 
 # Load specific language pairs
-eng_dataset = load_dataset("username/dataset-name", "eng")
-rus_dataset = load_dataset("username/dataset-name", "rus")
+eng_dataset = load_dataset("panagoa/tatoeba_kbd", "eng")
+rus_dataset = load_dataset("panagoa/tatoeba_kbd", "rus")
 
 # Example of accessing data
 for example in eng_dataset['train']: