Aamraz - Kurdish NLP collection
Overview
Aamraz which is written "ئامراز" in kurdish script means "instrument". This project is a collection of Natural Language Processing tools for Kurdish Language. Despite being spoken by millions, Kurdish remains an under-resourced language in Natural Language Processing (NLP). Recognizing the rich cultural heritage and historical significance of the Kurdish people, we—regardless of ethnicity—are committed to advancing tools and pre-trained models that empower the Kurdish language in modern research and technology. Our work aims to foster further development and provide a foundation for future research and applications in NLP. see github repository
Installation
pip install aamraz
Base Features
- Normalization
- Tokenization
- Stemming
- Word Embedding: Creates vector representations of words.
- Sentences Embedding: Creates vector representations of sentences.
Usage
import aamraz
# Normalization
normalizer= aamraz.Normalizer()
sample_sentence="قڵبەکەم بە کوردی قسە دەکات."
normalized_sentence=normalizer.normalize(sample_sentence)
print(normalized_sentence)
# Tokenization
tokenizer = aamraz.WordTokenizer()
sample_sentence="زوانی له دربره"
tokens = tokenizer.tokenize(sample_sentence)
print(tokens)
# Embedding by fasttext
model_path = 'kurdish_fasttext_skipgram_dim300_v1.bin'
embedding_model = aamraz.EmbeddingModel(model_path, dim=50)
sample_word="ئامراز"
sample_sentence="زوانی له دربره"
word_vector = embedding_model.word_embedding(sample_word)
sentence_vector = embedding_model.sentence_embedding(sample_sentence)
print(word_vector)
print(sentence_vector)
# Embedding by word2vec
model_path = 'kurdish_word2vec_model_dim100_v1.bin'
embedding_model = aamraz.EmbeddingModel(model_path, type='word2vec')
sample_word="ئامراز"
sample_sentence="زوانی له دربره"
word_vector = embedding_model.word_embedding(sample_word)
sentence_vector = embedding_model.sentence_embedding(sample_sentence)
print(word_vector)
print(sentence_vector)
# Stemming
stemmer=aamraz.Stemmer(method='simple')
stemmed=stemmer.stem("کتێبەکانمان")
print(stemmed)
Metadata
Release files for aamraz 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| aamraz-0.1.0.tar.gz | 10.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| aamraz-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 20.8 kB
Release files / aamraz-0.1.0.tar.gz
| Download URL | aamraz-0.1.0.tar.gz |
|---|---|
| Size | 10.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
2fa62ce66711a0436d39fa2a07140dc2b9a92eb3e939157f2f54849a2705154d
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BLAKE2b-256 checksum How to use checksums |
803ae215f33c52e27b0223400bbd6c9c0466de944566b9ec22801b9e234aa6e1
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.11.9
|
Release files / aamraz-0.1.0-py3-none-any.whl
| Download URL | aamraz-0.1.0-py3-none-any.whl |
|---|---|
| Size | 10.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
e261f08030a0a64391fccdd140fc2ba5321a183b7d3bf7f1aea4a843a1d46046
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6afe4003eec358ec3754bf161ee4774d18f2560346d5ad300d67d129155289ec
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.11.9
|