Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
deberta-v2
Generated from Trainer
Eval Results (legacy)
Instructions to use Gladiator/microsoft-deberta-v3-large_ner_conll2003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gladiator/microsoft-deberta-v3-large_ner_conll2003 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Gladiator/microsoft-deberta-v3-large_ner_conll2003")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Gladiator/microsoft-deberta-v3-large_ner_conll2003") model = AutoModelForTokenClassification.from_pretrained("Gladiator/microsoft-deberta-v3-large_ner_conll2003", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Gladiator/microsoft-deberta-v3-large_ner_conll2003: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/Gladiator/microsoft-deberta-v3-large_ner_conll2003/resolve/main/tokenizer.json
- Command line
-
hf download hf://Gladiator/microsoft-deberta-v3-large_ner_conll2003/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Gladiator/microsoft-deberta-v3-large_ner_conll2003/resolve/main/tokenizer.json
8.66 MB
File too large to display, you can check the raw version instead.