Instructions to use proxectonos/mdeberta-gl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use proxectonos/mdeberta-gl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="proxectonos/mdeberta-gl")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("proxectonos/mdeberta-gl") model = AutoModelForMaskedLM.from_pretrained("proxectonos/mdeberta-gl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31e55ee6d10d15f6cc885ce198b8f1b9de8d1d8c744c335712a2a5ccc9e0da30
- Size of remote file:
- 16.3 MB
- SHA256:
- 8d5a786a62a72797fcd2f23663c3f8665bc81e6f10043004c66490810b3d0d82
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