cornelliusyudhawijaya/abstracts_to_post_model

Model Card

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Example Usage

from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, pipeline

tokenizer = AutoTokenizer.from_pretrained('cornelliusyudhawijaya/abstracts_to_post_model', revision=None) # Load tokenizer
model = AutoModelForSeq2SeqLM.from_pretrained('cornelliusyudhawijaya/abstracts_to_post_model', revision=None) # Load model
pipe = pipeline('text2text-generation', model=model, tokenizer=tokenizer, pad_token_id=tokenizer.pad_token_id)

inputs = ['Note that not all scientists will apply, but there may be a handful.\n\nThe abstract can be downloaded from the papers cited in the paper for use within your project. We also recommend posting the results of the experiment, using our mailing list format, on these pages.\n\nFor other papers, see How to obtain the data from your source publication in NLP.\n\nThis project was last reported with NLP 3.10.6. The journal publishes NLP 3.10.6 once every seven years.']
print(pipe(inputs, max_length=512, do_sample=False))

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This model was trained with a synthetic dataset with DataDreamer 🤖💤. The synthetic dataset card and model card can be found here. The training arguments can be found here.