Seraphiive/FragmentOfBOOKCORPUS
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How to use Seraphiive/bert-personalized-PreAlpha-uncased with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("fill-mask", model="Seraphiive/bert-personalized-PreAlpha-uncased") # Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("Seraphiive/bert-personalized-PreAlpha-uncased")
model = AutoModelForMaskedLM.from_pretrained("Seraphiive/bert-personalized-PreAlpha-uncased")Pretrained model on English language using a masked language modeling (MLM) objective. Based on- Bert's base-uncased variant with the idea of fine-tuning and tweaking the model for a specific goal. This model is uncased: Meaning it does not make a difference between english and English.
Disclaimer: I do not own the rights for the architecture and basic model structure. I modified it according to my needs. However, The model still derives from bert-base-uncased, Taken from the huggingface's library of transformers.