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:
- 101c39ba5e7096de280fbe1f45608509971863794cde0d08a4d374eb2a19bdc8
- Size of remote file:
- 439 MB
- SHA256:
- 6fba0bf8ad1568fa6ff2e8bfbbb5dfb1984a6ac3a3dc6187bd51a6eb8a6722cf
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