|
--- |
|
language: no |
|
license: CC-BY 4.0 |
|
tags: |
|
- translation |
|
datasets: |
|
- oscar |
|
widget: |
|
- text: "Skriv inn en tekst som du ønsker å oversette til en annen målform." |
|
--- |
|
# Norwegian mT5 - Translation Bokmål Nynorsk |
|
|
|
## Description |
|
|
|
This is a sample reference model. |
|
|
|
Here is an example of how to use the model from Python |
|
```python |
|
# Import libraries |
|
from transformers import T5ForConditionalGeneration, AutoTokenizer |
|
model = T5ForConditionalGeneration.from_pretrained('andrek/nb2nn',from_flax=True) |
|
tokenizer = AutoTokenizer.from_pretrained('andrek/nb2nn') |
|
#Encode the text |
|
text = "Hun vil ikke gi bort sine personlige data." |
|
inputs = tokenizer.encode(text, return_tensors="pt") |
|
outputs = model.generate(inputs, max_length=255, num_beams=4, early_stopping=True) |
|
|
|
#Decode and print the result |
|
print(tokenizer.decode(outputs[0])) |
|
|
|
``` |
|
|
|
Or if you like to use the pipeline instead |
|
|
|
```python |
|
# Set up the pipeline |
|
from transformers import pipeline |
|
translator = pipeline("translation", model='andrek/nb2nn') |
|
|
|
# Do the translation |
|
text = "Hun vil ikke gi bort sine personlige data." |
|
print(translator(text, max_length=255)) |
|
|
|
``` |
