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:
- 7d6e3ae075693cce050a29caf3508b0b5aca1aae973dbadfdd93e8a90c59680e
- Size of remote file:
- 437 MB
- SHA256:
- d25f4c965893b2f0b429e2acde813f9d565da5bca8c0d231f963c5dbb76193d4
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