metadata
license: bigscience-bloom-rail-1.0
language:
- fa
Base Model: https://huggingface.co/bigscience/bloomz-7b1
Model fine-tuned on a real news dataset and optimized for neural news generation.
Note: Persian was not in pretraining.
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained("bigscience/bloomz-7b1")
model = AutoModelForSequenceClassification.from_pretrained('tum-nlp/neural-news-generator-bloomz-7b1-fa')
# Create the pipeline for neural news generation and set the repetition penalty >1.1 to punish repetition.
generator = pipeline('text-generation',
model=model,
tokenizer=tokenizer,
repetition_penalty=1.2)
# Define the prompt
prompt = " [EOP] به دنبال «شورش مسلحانه» مزدوران نظامی واگنر و تصرف برخی "
# Generate
generator(prompt, max_length=1000, num_return_sequences=1)
Trained on 6k datapoints (including all splits) from: https://huggingface.co/datasets/RohanAiLab/persian_news_dataset