# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/mrpc-bert-base-cased")
model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/mrpc-bert-base-cased")Quick Links
MRPC BERT base model (cased)
This is a sample model fine-tuned from the nlp_example_script.py using Accelerate and saved at the end.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/mrpc-bert-base-cased")