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:
- 526b72a5e55f62455dacff7d1700913351cd6378ac1826a00ac432db620ea33c
- Size of remote file:
- 2.86 kB
- SHA256:
- c5e3746bc423eca049b73c6dd2809532bc70474e2e8bd10b3fa74913b21c690d
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