Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use nickprock/distilbert-finetuned-ner-ontonotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nickprock/distilbert-finetuned-ner-ontonotes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nickprock/distilbert-finetuned-ner-ontonotes")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nickprock/distilbert-finetuned-ner-ontonotes") model = AutoModelForTokenClassification.from_pretrained("nickprock/distilbert-finetuned-ner-ontonotes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 497d0771252669f5a2e9c437c8c49aee31ffbb85673895795732b21cfcc907f0
- Size of remote file:
- 3.38 kB
- SHA256:
- cdef6db7ab3411330c80abd79f0c659c68624c05908a22beb3645247f1b55a60
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