BERT Models Finetuned on SCQA2 for Solar Cells
Collection
Train set: SCQA2 train set Test set: SCQA2 test set (SCQA2 contains first-turn, second-turn, and zero-index QA pairs in the Solar Cell QA Dataset) • 16 items • Updated
How to use CambridgeMolecularEngineering/bert-base-cased-scqa2 with Transformers:
# 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="CambridgeMolecularEngineering/bert-base-cased-scqa2") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("CambridgeMolecularEngineering/bert-base-cased-scqa2")
model = AutoModelForQuestionAnswering.from_pretrained("CambridgeMolecularEngineering/bert-base-cased-scqa2", device_map="auto")YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
epoch 4 step 488