educational_summarizer

1
license:apache-2.0
by
SeifElden2342532
Language Model
OTHER
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Quick Summary

AI model with specialized capabilities.

Code Examples

How to Usepythontransformers
from transformers import AutoTokenizer, LEDForConditionalGeneration

model_name = "SeifElden2342532/educational_summarizer"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = LEDForConditionalGeneration.from_pretrained(model_name)

ARTICLE_TO_SUMMARIZE = "..."

inputs = tokenizer(ARTICLE_TO_SUMMARIZE, return_tensors="pt")

# Generate Summary
summary_ids = model.generate(inputs["input_ids"], num_beams=4, max_length=500, early_stopping=True)
summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True, clean_up_tokenization_spaces=False)

print(summary)

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