Instructions to use dtorber/bert-base-spanish-wwm-cased_K5 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_K5 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_K5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dtorber/bert-base-spanish-wwm-cased_K5") model = AutoModelForSequenceClassification.from_pretrained("dtorber/bert-base-spanish-wwm-cased_K5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8d96f059cb253791783cb653bd1f9d6a52a0b50e0a9550d55790f488d76d039
- Size of remote file:
- 439 MB
- SHA256:
- 642bad73ed6e31fc6a23fb05d97211b07d0a1a78be6fd04e5e7861308dffc00d
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