Instructions to use austin/Austin-MeDeBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use austin/Austin-MeDeBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="austin/Austin-MeDeBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("austin/Austin-MeDeBERTa") model = AutoModelForMaskedLM.from_pretrained("austin/Austin-MeDeBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0614051f3dca702d6819e125fc5ee25638406779d737eab86d74501f1e23208c
- Size of remote file:
- 557 MB
- SHA256:
- 08e4cec284f7eddfb3d49f0ceddea39123b199b9968e273393010156ac5ad97b
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