Instructions to use dccuchile/albert-large-spanish-finetuned-qa-mlqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dccuchile/albert-large-spanish-finetuned-qa-mlqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="dccuchile/albert-large-spanish-finetuned-qa-mlqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("dccuchile/albert-large-spanish-finetuned-qa-mlqa") model = AutoModelForQuestionAnswering.from_pretrained("dccuchile/albert-large-spanish-finetuned-qa-mlqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8cd30b4c39cee7ade9d8f912fdd99cbf918ba802dbc17dc28ecd1e2cff8e5eee
- Size of remote file:
- 67.1 MB
- SHA256:
- 350031c574de5a92c8f83a78caaffaf2e9d905f28e01d7b3d0037606bcc7bed0
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