Instructions to use claudiaMartinez1982/bert-base-spanish-wwm-cased_bs4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use claudiaMartinez1982/bert-base-spanish-wwm-cased_bs4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="claudiaMartinez1982/bert-base-spanish-wwm-cased_bs4")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("claudiaMartinez1982/bert-base-spanish-wwm-cased_bs4") model = AutoModelForTokenClassification.from_pretrained("claudiaMartinez1982/bert-base-spanish-wwm-cased_bs4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e8f969f31d9e6815a7402f1052e394011dc41d0d59f047a0ab728e3959a0511
- Size of remote file:
- 5.3 kB
- SHA256:
- 513f8f80af98d6885ad4f2d5ff2848a3f8acaf786f4108dab4933cd51dc9214a
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