Bengali Language Model
Project description
Bengal Language Model
Bengali language model is build with fastai's ULMFit and ready for prediction
and classfication
task.
NB:
- This tool mostly followed inltk
- We separated
Bengali
part with better evaluation results
Installation
pip install bnlm
Evaluation Result
Language Model
- Accuracy 48.26% on validation dataset
- Perplexity: ~22.79
Training
To train with your own corpus follow this repository
Features and API
Download pretrained Model
To start, first download pretrained Language Model and Sentencepiece model
from bnlm.bnlm import download_models
download_models()
Predict N Words
from bnlm.bnlm import BengaliTokenizer
from bnlm.bnlm import predict_n_words
model_path = 'model'
input_sen = "আমি বাজারে"
output = predict_n_words(input_sen, 3, model_path)
print("Word Prediction: ", output)
Get Sentence Encoding
from bnlm.bnlm import BengaliTokenizer
from bnlm.bnlm import get_sentence_encoding
model_path = 'model'
sp_model = "model/bn_spm.model"
input_sentence = "আমি ভাত খাই।"
encoding = get_sentence_encoding(input_sentence, model_path, sp_model)
print("sentence encoding is: ", encoding)
Get Embedding Vectors
from bnlm.bnlm import BengaliTokenizer
from bnlm.bnlm import get_embedding_vectors
model_path = 'model'
sp_model = "model/bn_spm.model"
input_sentence = "আমি ভাত খাই।"
embed = get_embedding_vectors(input_sentence, model_path, sp_model)
print("sentence embedding is : ", embed)
Sentence Similarity
from bnlm.bnlm import BengaliTokenizer
from bnlm.bnlm import get_sentence_encoding
from bnlm.bnlm import get_similar_sentences
model_path = 'model'
sp_model = "model/bn_spm.model"
sentence_1 = "আমি ভাত খাই।"
sentence_2 = "আমি ভাত খাই।"
sim = get_sentence_similarity(sentence_1, sentence_2, model_path, sp_model)
print("similarity is: ", sim)
Get Simillar Sentences
from bnlm.bnlm import BengaliTokenizer
from bnlm.bnlm import get_embedding_vectors
from bnlm.bnlm import get_similar_sentences
model_path = 'model'
sp_model = "model/bn_spm.model"
input_sentence = "আমি ভাত খাই।"
sen_pred = get_similar_sentences(input_sentence, 3, model_path, sp_model)
print(sen_pred)
Classification
upcomming
Project details
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