Instructions to use deprem-ml/deprem-ner-mdebertav3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deprem-ml/deprem-ner-mdebertav3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="deprem-ml/deprem-ner-mdebertav3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("deprem-ml/deprem-ner-mdebertav3") model = AutoModelForTokenClassification.from_pretrained("deprem-ml/deprem-ner-mdebertav3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39726eb5340ba12de4d52140577ab4b60583184fc347b8e4f17192ff8d630742
- Size of remote file:
- 3.52 kB
- SHA256:
- 09bb5d9dbb6337c6490cdbdf41cfe94c785983c80a23b84c6c88312b6c7b52b4
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