Instructions to use plncmm/mdeberta-cowese-base-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use plncmm/mdeberta-cowese-base-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="plncmm/mdeberta-cowese-base-es")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("plncmm/mdeberta-cowese-base-es") model = AutoModelForMaskedLM.from_pretrained("plncmm/mdeberta-cowese-base-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 140cfd06af13e9ac0b45925d10e26d6c57b9812cc688e8824a709da2e72f2895
- Size of remote file:
- 1.11 GB
- SHA256:
- deb009951d308a92ec4457ba66eb1ed1a83ed407020c3a56caa75a16cc6bad9c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.