Token Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use harsh13333/ner_bert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harsh13333/ner_bert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="harsh13333/ner_bert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("harsh13333/ner_bert_model") model = AutoModelForTokenClassification.from_pretrained("harsh13333/ner_bert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4274adfcfed651afd106deb2b7af10c2e2a127f42fe576f6a940b6ef82cdaef3
- Size of remote file:
- 4.92 kB
- SHA256:
- 27e6d320801724363021664cd6a5bbe52574242180347e20572ec0b4dd9de81e
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