Instructions to use plncmm/mdeberta-wl-base-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use plncmm/mdeberta-wl-base-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="plncmm/mdeberta-wl-base-es")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("plncmm/mdeberta-wl-base-es") model = AutoModelForMaskedLM.from_pretrained("plncmm/mdeberta-wl-base-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ceed08c50e3f8254f284c7854ee8f93876e4bb2e3725622cd298c8c3a846322
- Size of remote file:
- 1.11 GB
- SHA256:
- 57d32f66c0b9da878234d132e8bda518e43cf2cc72879b9142da7da0601f8a9b
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