Instructions to use Omar2027/Author_identification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Omar2027/Author_identification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Omar2027/Author_identification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Omar2027/Author_identification") model = AutoModelForMaskedLM.from_pretrained("Omar2027/Author_identification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
The dataset contains authors with a text data that can help identify the article by their books, books are from the first 3 centuries after Hijra.c3e5ef9 -
initial commit
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