Instructions to use claudiaMartinez1982/bert-base-spanish-wwm-cased_bs32 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_bs32 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_bs32")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("claudiaMartinez1982/bert-base-spanish-wwm-cased_bs32") model = AutoModelForTokenClassification.from_pretrained("claudiaMartinez1982/bert-base-spanish-wwm-cased_bs32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33a07aadfbcb2dbc739e6bd9d040cb9048021ca3e0be86f22d15426aa2d611cb
- Size of remote file:
- 437 MB
- SHA256:
- 8ea815d9ee8392048c11fbd97bde3a02c23c58c73cf812a8df5e84f406cc3aba
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