Instructions to use dccuchile/bert-base-spanish-wwm-cased-finetuned-qa-mlqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dccuchile/bert-base-spanish-wwm-cased-finetuned-qa-mlqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="dccuchile/bert-base-spanish-wwm-cased-finetuned-qa-mlqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("dccuchile/bert-base-spanish-wwm-cased-finetuned-qa-mlqa") model = AutoModelForQuestionAnswering.from_pretrained("dccuchile/bert-base-spanish-wwm-cased-finetuned-qa-mlqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 194 Bytes
6072f94 | 1 2 3 4 5 6 7 8 | {
"epoch": 3.0,
"train_loss": 1.556812895637894,
"train_runtime": 24717.2821,
"train_samples": 82070,
"train_samples_per_second": 9.961,
"train_steps_per_second": 0.623
} |