Metadata-Version: 2.1
Name: aimped
Version: 0.1.36
Summary: Aimped is a unique library that provides classes and functions for only exclusively business-tailored AI-based NLP models.
Home-page: https://dev.ml-hub.nioyatechai.com/
Author: Russell C.
Author-email: russell@aimped.com
Maintainer: aimped
Maintainer-email: contact@aimped.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# **aimped**
![aimped](https://dev.ml-hub.nioyatechai.com/static/media/AimpedBirdLogo.0b3c7cc26d31afe7bd73db496acb01d1.svg)

**Aimped is a unique python library that provides classes and functions for only exclusively business-tailored AI-based NLP models.**  

# Installation  
```python
pip install aimped
```

# Usage  
```python  
import aimped
print(aimped.__version__)
```
## Examples  

### Example 1

```python  
from aimped import nlp

result = nlp.sentence_tokenizer("Hi, welcome to aimped. Explore ai models.",language="english")
print(result)
# ['Hi, welcome to aimped.', 'Explore ai models.']
```

### Example 2
```python  
from aimped.nlp.tokenizer import sentence_tokenizer

result = sentence_tokenizer("Hi, welcome to aimped. Explore ai models.",language="english")
print(result)
# ['Hi, welcome to aimped.', 'Explore ai models.']
```

### Example 3
```python  
from aimped.nlp.pipeline import Pipeline

pipe = Pipeline(model=model, tokenizer=tokenizer, device='cpu')
result = pipe.ner_result(
                        text=text,
                        sents_tokens_list=sents_tokens_list,
                        sentences=sentences)
print(result)
```
### Example 4
```python  
from aimped.nlp.pipeline import Pipeline
text = """Trotz aller medizinischen Interventionen konnte der bei dem Verkehrsunfall schwer verletzte Fahrer des Fahrzeugs nicht gerettet werden."""

pipe = Pipeline(model=model, tokenizer=tokenizer, device='cpu')
result = pipe.translation_result(
                        text=[text],
                        source_language = "german",
                        output_language = "english")
print(result)
# ['Despite all medical interventions, the driver of the vehicle who was severely injured in the traffic accident could not be saved.']
```


