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:
- 748a2e46d14ea5ad8bc68f94858da185fae0c2ae9f7d4059ab2d948ee1944801
- Size of remote file:
- 1.11 GB
- SHA256:
- ce63d98d63447ee96d1bad8ffcce9cb618b935ec6dc604eebcbb70cf2c8978e5
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