DatarrX
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myX-Tokenizer-Unigram

Feature Extraction

Burmese

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 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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-## Model Details
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 ---
+license: apache-2.0
+datasets:
+- kalixlouiis/raw-data
+language:
+- my
+pipeline_tag: feature-extraction
 ---
+# DatarrX - myX-Tokenizer-Unigram ⚙️
+**myX-Tokenizer-Unigram** is a specialized tokenizer for the Burmese language based on the **Unigram Language Model** algorithm. Developed by [**Khant Sint Heinn (Kalix Louis)**](https://huggingface.co/kalixlouiis) under [**DatarrX (Myanmar Open Source NGO)**](https://huggingface.co/DatarrX), this model is optimized for linguistic probabilistic segmentation.
+## 🎯 Objectives & Characteristics
+* **Unigram Excellence:** Utilizes a probabilistic subword tokenization method that often aligns better with the morphological structure of the Burmese language than BPE.
+* **Native Burmese Specialist:** Trained exclusively on a massive Burmese-only corpus to ensure high-fidelity script recognition.
+* **Optimized Efficiency:** Developed using high-quality sampling to balance performance and model size.
+## 🛠️ Technical Specifications
+* **Algorithm:** Unigram Language Model.
+* **Vocabulary Size:** 64,000.
+* **Normalization:** NFKC.
+* **Features:** Byte-fallback, Split Digits, and Dummy Prefix.
 ### Training Data
+Trained on the [kalixlouiis/raw-data](https://huggingface.co/datasets/kalixlouiis/raw-data) dataset, specifically utilizing **1.5 million** cleaned Burmese sentences.
+## ⚠️ Important Considerations (Limitations)
+* **Limited English Support:** This model is strictly a Burmese script specialist. It has significant limitations in processing English text, which may result in excessive subword splitting for Latin characters.
+* **Script Sensitivity:** Optimized for modern Burmese script; performance may vary with older orthography or heavy use of specialized Pali/Sanskrit loanwords.
+---
+# DatarrX - myX-Tokenizer-Unigram (မြန်မာဘာသာ)
+**myX-Tokenizer-Unigram** သည် Unigram Language Model algorithm ကို အသုံးပြု၍ မြန်မာဘာသာစကားအတွက် အထူးပြုလုပ်ထားသော Tokenizer ဖြစ်ပါသည်။ ဤ Model ကို [**DatarrX (Myanmar Open Source NGO)**](https://huggingface.co/DatarrX) မှ ထုတ်ဝေခြင်းဖြစ်ပြီး [**Khant Sint Heinn (Kalix Louis)**](https://huggingface.co/kalixlouiis) မှ အဓိက ဖန်တီးတည်ဆောက်ထားခြင်း ဖြစ်ပါသည်။
+## 🎯 ရည်ရွယ်ချက်နှင့် ထူးခြားချက်များ
+* **Unigram ၏ အားသာချက်:** BPE ထက် ပိုမို၍ ဖြစ်နိုင်ခြေ (Probability) အပေါ် အခြေခံကာ ဖြတ်တောက်သဖြင့် မြန်မာစာ၏ ဝဏ္ဏဗေဒ သဘာဝနှင့် ပိုမိုကိုက်ညီစေရန်။
+* **မြန်မာစာ အထူးပြု:** ဤ Model ကို မြန်မာစာ သီးသန့်ဖြင့်သာ Train ထားသဖြင့် ဗမာ(မြန်မာ)စာသားများ၏ အနက်အဓိပ္ပာယ်ကို ပိုမိုတိကျစွာ ဖြတ်တောက်နိုင်ရန်။
+* **စနစ်တကျ လေ့ကျင့်မှု:** စာကြောင်းပေါင်း ၁.၅ သန်းကို အသုံးပြု၍ အရည်အသွေးမြင့် စံနှုန်းများဖြင့် တည်ဆောက်ထားပါသည်။
+## 🛠️ နည်းပညာဆိုင်ရာ အချက်အလက်များ
+* **Algorithm:** Unigram Language Model။
+* **Vocab Size:** 64,000။
+* **Normalization:** NFKC။
+* **Features:** Byte-fallback, Split Digits နှင့် Dummy Prefix အင်္ဂါရပ်များ ပါဝင်ပါသည်။
+### အသုံးပြုထားသော Dataset
+[kalixlouiis/raw-data](https://huggingface.co/datasets/kalixlouiis/raw-data) ထဲမှ သန့်စင်ပြီးသား မြန်မာစာကြောင်းပေါင်း **၁.၅ သန်း (1.5 Million)** ကို အသုံးပြုထားပါသည်။
+## ⚠️ သိထားရန် ကန့်သတ်ချက်များ
+* **အင်္ဂလိပ်စာ အားနည်းမှု:** ဤ Model သည် မြန်မာစာ သီးသန့်အတွက်သာ ဖြစ်သောကြောင့် အင်္ဂလိပ်စာလုံးများကို ဖြတ်တောက်ရာတွင် အလွန်အားနည်းပြီး စာလုံးအသေးလေးများအဖြစ် ကွဲထွက်သွားတတ်ပါသည်။
+* **အရေးအသား စံနှုန်း:** ခေတ်သစ်မြန်မာစာ အရေးအသားအပေါ် အခြေခ��ထားသဖြင့် ပါဠိ/သက္ကတ အသုံးများသော စာသားများတွင် ဖြတ်တောက်ပုံ ကွဲပြားနိုင်ပါသည်။
+---
+## 💻 How to Use (အသုံးပြုနည်း)
+```python
+import sentencepiece as spm
+from huggingface_hub import hf_hub_download
+model_path = hf_hub_download(repo_id="DatarrX/myX-Tokenizer-Unigram", filename="myX-Tokenizer.model")
+sp = spm.SentencePieceProcessor(model_file=model_path)
+text = "မြန်မာစာကို Unigram algorithm နဲ့ စနစ်တကျ ဖြတ်တောက်ကြည့်ခြင်း။"
+print(sp.encode_as_pieces(text))
+```
+# ✍️ Project Authors
+- Developer: [**Khant Sint Heinn (Kalix Louis)**](https://huggingface.co/kalixlouiis)
+- Organization: [**DatarrX (Myanmar Open Source NGO)**](https://huggingface.co/DatarrX)