BERT Models Finetuned on SCQA1 for Solar Cells
Collection
Train set: SCQA1 Test set: SCQA1 (SCQA1 is the first-turn QA pairs in the Solar Cell QA Dataset) • 16 items • Updated
How to use CambridgeMolecularEngineering/bert-base-uncased-scqa1 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-uncased-scqa1") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("CambridgeMolecularEngineering/bert-base-uncased-scqa1")
model = AutoModelForQuestionAnswering.from_pretrained("CambridgeMolecularEngineering/bert-base-uncased-scqa1", device_map="auto")YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
epoch 4, step 432