Update README.md

README.md

@@ -15,12 +15,13 @@ language:
 
 ### Overview
 
-This repository introduces the first comprehensive public collection of resources for the **Tigre** language — an under-resourced South Semitic language within the Afro-Asiatic family. The release aggregates multiple modalities (text + speech) and provides baseline models for several core NLP tasks including language modeling, ASR, and machine translation.
+This repository introduces the first comprehensive public collection of resources for the Tigre language — an under-resourced South Semitic language within the Afro-Asiatic family. The release aggregates multiple modalities (text + speech) and provides baseline models for several core NLP tasks including language modeling, ASR, and machine translation.
 The models were trained on a substantial Tigre corpus and are valuable for any downstream Natural Language Processing (NLP) task, especially those involving this low-resource language.
 
 ## What are FastText Embeddings?
 
-FastText is an extension of the popular Word2Vec model, which represents words as dense, real-valued vectors in a multi-dimensional space. The key advantage of FastText is that it represents each word as a bag of character n-grams (subwords). This subword information allows the model to:
+FastText is an extension of the popular Word2Vec model, which represents words as dense, real-valued vectors in a multi-dimensional space. 
+The key advantage of FastText is that it represents each word as a bag of character n-grams (subwords). This subword information allows the model to:
 
 1. Generate vectors for out-of-vocabulary (OOV) words (e.g., typos or unseen compounds) by summing the vectors of their character n-grams.
 2. Capture morphological structure, which is crucial for morphologically rich languages like Tigre, where words have complex prefixes and suffixes.
@@ -29,6 +30,7 @@ FastText is an extension of the popular Word2Vec model, which represents words a
 
 - tig.bin: The binary FastText model (full model), which allows for querying subword vectors and OOV words.
 - tigre.vec: A plain text file containing only the full word vectors, compatible with tools like gensim and used for downstream tasks or visualizations.
+  
 ---
 
 ## Model Training & Data Curation
@@ -104,7 +106,7 @@ import fasttext
 
 # Download the bin file
 bin_path = hf_hub_download(
-    repo_id="<Your_HF_Repo_Name>/tigre-data-fasttext", # Replace <Your_HF_Repo_Name>
+    repo_id="BeitTigreAI/tigre-data-fasttext", 
     filename="tig.bin",
     repo_type="dataset"
 )
@@ -124,11 +126,11 @@ Nearest neighbors for 'ሻም': [(0.55, 'ሻማት'), (0.53, 'ዴሪር'), (0.46
 
 ## Dataset Structure
 
-tigre-data-fasttext/\n
-├── README.md\n
-├── config.json\n
-├── tig.bin\n
-├── tigre.vec\n
+tigre-data-fasttext/  
+├── README.md  
+├── config.json  
+├── tig.bin  
+├── tigre.vec  
 
 ---