Instructions to use codeaze/deberta_med_22feb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codeaze/deberta_med_22feb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="codeaze/deberta_med_22feb")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("codeaze/deberta_med_22feb") model = AutoModelForTokenClassification.from_pretrained("codeaze/deberta_med_22feb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a839ade26d1757d4d7480ff38b7f2a695bc507dab2ac367480f42901665678a
- Size of remote file:
- 1.74 GB
- SHA256:
- b40f93e7991007b85e8ae1f357349f146a2328d0a4f846dae5eeb561fc6c7da4
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