Instructions to use dtorber/bert-base-spanish-wwm-cased_K3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/bert-base-spanish-wwm-cased_K3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dtorber/bert-base-spanish-wwm-cased_K3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dtorber/bert-base-spanish-wwm-cased_K3") model = AutoModelForSequenceClassification.from_pretrained("dtorber/bert-base-spanish-wwm-cased_K3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5048df27936eee961564e803f241a28860b103073ab8c507d3d17e557ff2291b
- Size of remote file:
- 4.86 kB
- SHA256:
- f3abe738c08ecb8c9be74494395d98535bc408fd7d1fa2b21944cba0f119afd9
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