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