parsi-ai-nlpclass / PersianEase

huggingface.co
Total runs: 3
24-hour runs: 0
7-day runs: 0
30-day runs: 3
Model's Last Updated: March 04 2024
text-generation

Introduction of PersianEase

Model Details of PersianEase

PersianEase

This model is fine-tuned to generate informal text from formal text based on the input provided. It has been fine-tuned on [Mohavere Dataset] (Takalli vahideh, Kalantari, Fateme, Shamsfard, Mehrnoush, Developing an Informal-Formal Persian Corpus, 2022.) using the pretrained model persian-t5-formality-transfer .

Evaluation Metrics
Metric Basic Model Base Persian T5 Previous Semester Model Our Model
BLEU-1 0.269 0.256 0.397 0.664
BLEU-2 0.137 0.171 0.299 0.539
BLEU-3 0.084 0.121 0.231 0.444
BLEU-4 0.054 0.086 0.177 0.364
Bert-Score Precision 0.581 0.583 0.665 0.826
Bert-Score Recall 0.629 0.614 0.659 0.820
Bert-Score F1 Score 0.603 0.595 0.658 0.822
ROUGE-1 F1 Score 0.259 - - 0.701
ROUGE-2 F1 Score 0.061 - - 0.475
ROUGE-l F1 Score 0.250 - - 0.675
Usage

from transformers import (T5ForConditionalGeneration, AutoTokenizer, pipeline)
import torch

model = T5ForConditionalGeneration.from_pretrained('parsi-ai-nlpclass/PersianEase')
tokenizer = AutoTokenizer.from_pretrained('parsi-ai-nlpclass/PersianEase')

pipe = pipeline(task='text2text-generation', model=model, tokenizer=tokenizer)
def test_model(text):
  device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')  
  model.to(device) 

  inputs = tokenizer.encode("formal: " + text, return_tensors='pt', max_length=128, truncation=True, padding='max_length')
  inputs = inputs.to(device) 

  outputs = model.generate(inputs, max_length=128, num_beams=4, temperature=0.7)
  print("Output:", tokenizer.decode(outputs[0], skip_special_tokens=True))  

text = "   من فقط می‌خواستم بگویم که چقدر قدردان همه چیزهایی هستم که برای من انجام داده ای."
print("Original:", text)
test_model(text)

# output: من فقط میخوام بگم که چقدر قدردان همه کاریم که برای من انجام دادی. دوستی تو برای من یه هدیه بزرگه و من همیشه از داشتن یه دوست مثل تو خوشحالم.

text = "   آرزویش است او را یک رستوران ببرم."
print("Original:", text)
test_model(text)

# output: آرزوشه یه رستوران ببرمش

Runs of parsi-ai-nlpclass PersianEase on huggingface.co

3
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
3
30-day runs

More Information About PersianEase huggingface.co Model

More PersianEase license Visit here:

https://choosealicense.com/licenses/mit

PersianEase huggingface.co

PersianEase huggingface.co is an AI model on huggingface.co that provides PersianEase's model effect (), which can be used instantly with this parsi-ai-nlpclass PersianEase model. huggingface.co supports a free trial of the PersianEase model, and also provides paid use of the PersianEase. Support call PersianEase model through api, including Node.js, Python, http.

parsi-ai-nlpclass PersianEase online free

PersianEase huggingface.co is an online trial and call api platform, which integrates PersianEase's modeling effects, including api services, and provides a free online trial of PersianEase, you can try PersianEase online for free by clicking the link below.

parsi-ai-nlpclass PersianEase online free url in huggingface.co:

https://huggingface.co/parsi-ai-nlpclass/PersianEase

PersianEase install

PersianEase is an open source model from GitHub that offers a free installation service, and any user can find PersianEase on GitHub to install. At the same time, huggingface.co provides the effect of PersianEase install, users can directly use PersianEase installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

PersianEase install url in huggingface.co:

https://huggingface.co/parsi-ai-nlpclass/PersianEase

Url of PersianEase

Provider of PersianEase huggingface.co

parsi-ai-nlpclass
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