Instructions to use medspaner/mdeberta-v3-base-re-ct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use medspaner/mdeberta-v3-base-re-ct with Transformers:
# Load model directly from transformers import AutoTokenizer, DebertaV2ForRelationExtraction tokenizer = AutoTokenizer.from_pretrained("medspaner/mdeberta-v3-base-re-ct") model = DebertaV2ForRelationExtraction.from_pretrained("medspaner/mdeberta-v3-base-re-ct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01c5cfcfa4b9503f0d43d659662de651ae1eef121e22a5e808abe4cef21cc7fb
- Size of remote file:
- 1.11 GB
- SHA256:
- 660cc1f4283effc845fdacc7212bdae31757e0d1aac798a2711796bf8371ab72
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