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--- |
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language: bm |
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tags: |
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- bambara |
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- fasttext |
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- embeddings |
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- word-vectors |
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- african-nlp |
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- low-resource |
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license: apache-2.0 |
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datasets: |
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- bambara-corpus |
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metrics: |
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- cosine_similarity |
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pipeline_tag: feature-extraction |
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--- |
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# Bambara FastText Embeddings |
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## Model Description |
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This model provides FastText word embeddings for the Bambara language (Bamanankan), a Mande language spoken primarily in Mali. The embeddings capture semantic relationships between Bambara words and enable various NLP tasks for this low-resource African language. |
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**Model Type:** FastText Word Embeddings |
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**Language:** Bambara (bm) |
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**License:** Apache 2.0 |
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## Model Details |
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### Model Architecture |
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- **Algorithm:** FastText with subword information |
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- **Vector Dimension:** 300 |
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- **Vocabulary Size:** 9,973 unique Bambara words |
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- **Training Method:** Skip-gram with negative sampling |
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- **Subword Information:** Character n-grams (enables handling of out-of-vocabulary words) |
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### Training Data |
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The model was trained on Bambara text corpora, building upon the work of David Ifeoluwa Adelani's research on African language embeddings. |
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### Intended Use |
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This model is designed for: |
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- **Semantic similarity tasks** in Bambara |
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- **Information retrieval** for Bambara documents |
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- **Cross-lingual research** involving Bambara |
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- **Cultural preservation** and digital humanities projects |
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- **Educational applications** for Bambara language learning |
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- **Foundation for downstream NLP tasks** in Bambara |
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## Usage |
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``` |
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Coming soon |
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``` |
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