PiC/phrase_retrieval
Updated • 59 • 5
How to use Deehan1866/PR-pass-xlnet-base-cased with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="Deehan1866/PR-pass-xlnet-base-cased") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("Deehan1866/PR-pass-xlnet-base-cased")
model = AutoModelForQuestionAnswering.from_pretrained("Deehan1866/PR-pass-xlnet-base-cased", device_map="auto")This model is a fine-tuned version of xlnet/xlnet-base-cased on the PiC/phrase_retrieval PR-pass dataset.
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The following hyperparameters were used during training:
Base model
xlnet/xlnet-base-cased