Instructions to use dccuchile/bert-base-spanish-wwm-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dccuchile/bert-base-spanish-wwm-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dccuchile/bert-base-spanish-wwm-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dccuchile/bert-base-spanish-wwm-uncased") model = AutoModelForMaskedLM.from_pretrained("dccuchile/bert-base-spanish-wwm-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
updating all configs, adding both fast and legacy tokenizers, also adding tensorflow checkpoint for compatibility
27c33d2 - Xet hash:
- a2a229ec86bf0bdae83412c26ad306e0ebe65e407147e91ac576e40b5a0249f8
- Size of remote file:
- 537 MB
- SHA256:
- 07e82361c425346a2d05b8f7ed638388e1f617416e2d9763224ff96ca0914e18
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.