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:
- d1b97d37db4edebff2e7312d459d34ccc1e5bc4cdc3bba52a4f8ba2831a9a0b2
- Size of remote file:
- 5.3 kB
- SHA256:
- 46e1764ca4bec45f5a445e9e44126dadd7c4389c33f5a58b84f7cf122f9b2117
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