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:
- 0a01d7396257e5e4c9d9495d7aa9dbe9e552700139f8c48b24b7d0251a833800
- Size of remote file:
- 4.98 kB
- SHA256:
- 8a7e602cffbdfa225158706d6aeff3ac8d999df78932ffe6d9dac1ea6c0960ff
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