Token Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use chintagunta85/test_ner3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chintagunta85/test_ner3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chintagunta85/test_ner3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("chintagunta85/test_ner3") model = AutoModelForTokenClassification.from_pretrained("chintagunta85/test_ner3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b0fabccddef1d907d6463fb48038334a7460c2d01222ec2bf419481f2012cc5
- Size of remote file:
- 266 MB
- SHA256:
- fc86c9bb1f622af205a2f01eee86968f0c10eb9c5c2f2eee1c8cf5aed884ed76
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