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:
- 22d073c499e9c9918b6c16b4e061cd8f80260337481506baa8eb8a8a145fbd13
- Size of remote file:
- 4.86 kB
- SHA256:
- 5db7c9c7cd539f4576d1ed462d4af8568cefbae0611f647611c06498b2dd09a0
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