# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("philschmid/distilbert-neuron")
model = AutoModelForQuestionAnswering.from_pretrained("philschmid/distilbert-neuron", device_map="auto")Quick Links
AWS Neuron Conversion of distilbert-base-cased-distilled-squad
DistilBERT base cased distilled SQuAD
This model is a fine-tune checkpoint of DistilBERT-base-cased, fine-tuned using (a second step of) knowledge distillation on SQuAD v1.1. This model reaches a F1 score of 87.1 on the dev set (for comparison, BERT bert-base-cased version reaches a F1 score of 88.7).
- Downloads last month
- 45
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="philschmid/distilbert-neuron")