# Bangla Sentence Transformer

 Sentence Transformer is a cutting-edge natural language processing (NLP) model that is capable of encoding and transforming sentences into high-dimensional embeddings. With this technology, we can unlock powerful insights and applications in various fields like text classification, information retrieval, semantic search, and more.

This model is finetuned from ```stsb-xlm-r-multilingual``` 
 It's now available on Hugging Face! 🎉🎉

## Install
## Usage (Sentence-Transformers)
Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:

```
pip install -U sentence-transformers
```

```python
from sentence_transformers import SentenceTransformer
sentences = ['আমি আপেল খেতে পছন্দ করি। ', 'আমার একটি আপেল মোবাইল আছে।','আপনি কি এখানে কাছাকাছি থাকেন?', 'আশেপাশে কেউ আছেন?']

model = SentenceTransformer('shihab17/bangla-sentence-transformer')
embeddings = model.encode(sentences)
print(embeddings)
```

```python
from transformers import AutoTokenizer, AutoModel
import torch


#Mean Pooling - Take attention mask into account for correct averaging
def mean_pooling(model_output, attention_mask):
    token_embeddings = model_output[0] #First element of model_output contains all token embeddings
    input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
    return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)


# Sentences we want sentence embeddings for
sentences = ['আমি আপেল খেতে পছন্দ করি। ', 'আমার একটি আপেল মোবাইল আছে।','আপনি কি এখানে কাছাকাছি থাকেন?', 'আশেপাশে কেউ আছেন?']

# Load model from HuggingFace Hub
tokenizer = AutoTokenizer.from_pretrained('shihab17/bangla-sentence-transformer')
model = AutoModel.from_pretrained('shihab17/bangla-sentence-transformer')

# Tokenize sentences
encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')

# Compute token embeddings
with torch.no_grad():
    model_output = model(**encoded_input)

# Perform pooling. In this case, mean pooling.
sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask'])

print("Sentence embeddings:")
print(sentence_embeddings)
```

## How to get sentence similarity

```python
from sentence_transformers import SentenceTransformer
from sentence_transformers.util import pytorch_cos_sim


transformer = SentenceTransformer('shihab17/bangla-sentence-transformer')

sentences = ['আমি আপেল খেতে পছন্দ করি। ', 'আমার একটি আপেল মোবাইল আছে।','আপনি কি এখানে কাছাকাছি থাকেন?', 'আশেপাশে কেউ আছেন?']

sentences_embeddings = transformer.encode(sentences)

for i in range(len(sentences)):
    for j in range(i, len(sentences)):
        sen_1 = sentences[i]
        sen_2 = sentences[j]
        sim_score = float(pytorch_cos_sim(sentences_embeddings[i], sentences_embeddings[j]))
        print(sen_1, '----->', sen_2, sim_score)
```

## Best MSE: 7.57528096437454
{"language": ["bn", "en"], "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"}
sentence-transformers pytorch xlm-roberta feature-extraction sentence-similarity bn en endpoints_compatible region:us
TAGS
#sentence-transformers #pytorch #xlm-roberta #feature-extraction #sentence-similarity #bn #en #endpoints_compatible #region-us 

# Bangla Sentence Transformer

 Sentence Transformer is a cutting-edge natural language processing (NLP) model that is capable of encoding and transforming sentences into high-dimensional embeddings. With this technology, we can unlock powerful insights and applications in various fields like text classification, information retrieval, semantic search, and more.

This model is finetuned from  
 It's now available on Hugging Face! 

## Install
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed:







## How to get sentence similarity



## Best MSE: 7.57528096437454
# Bangla Sentence Transformer

 Sentence Transformer is a cutting-edge natural language processing (NLP) model that is capable of encoding and transforming sentences into high-dimensional embeddings. With this technology, we can unlock powerful insights and applications in various fields like text classification, information retrieval, semantic search, and more.

This model is finetuned from  
 It's now available on Hugging Face! ## Install ## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed: ## How to get sentence similarity ## Best MSE: 7.57528096437454
TAGS
#sentence-transformers #pytorch #xlm-roberta #feature-extraction #sentence-similarity #bn #en #endpoints_compatible #region-us 
 # Bangla Sentence Transformer

 Sentence Transformer is a cutting-edge natural language processing (NLP) model that is capable of encoding and transforming sentences into high-dimensional embeddings. With this technology, we can unlock powerful insights and applications in various fields like text classification, information retrieval, semantic search, and more.

This model is finetuned from  
 It's now available on Hugging Face! ## Install ## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed: ## How to get sentence similarity ## Best MSE: 7.57528096437454