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:
- caf1923afd036fa2197da43cdf8bb3868abf34e37174508a0698bb3489c13a4d
- Size of remote file:
- 16.3 MB
- SHA256:
- 6f06fc3bbcbbc8f07be861b9a6a69e177247bc549b2bcbf0483e4dd98c06b6f6
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