Instructions to use haritzpuerto/spanbert-large-cased_QAMR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use haritzpuerto/spanbert-large-cased_QAMR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="haritzpuerto/spanbert-large-cased_QAMR")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("haritzpuerto/spanbert-large-cased_QAMR") model = AutoModelForQuestionAnswering.from_pretrained("haritzpuerto/spanbert-large-cased_QAMR") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("haritzpuerto/spanbert-large-cased_QAMR")
model = AutoModelForQuestionAnswering.from_pretrained("haritzpuerto/spanbert-large-cased_QAMR")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="haritzpuerto/spanbert-large-cased_QAMR")