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:
- a595e21626b927470c6a5939a97146b02f8e0f2ae3dbdd99cac36afb9e040a2a
- Size of remote file:
- 439 MB
- SHA256:
- 7333d230267bf15df1d2bfa17a4e125a3cdb0ddc02d0f4b419662250a3f7c304
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