Token Classification
Transformers
PyTorch
TensorBoard
deberta
Generated from Trainer
Eval Results (legacy)
Instructions to use geckos/deberta-base-fine-tuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use geckos/deberta-base-fine-tuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="geckos/deberta-base-fine-tuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("geckos/deberta-base-fine-tuned-ner") model = AutoModelForTokenClassification.from_pretrained("geckos/deberta-base-fine-tuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from geckos/deberta-base-fine-tuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/geckos/deberta-base-fine-tuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://geckos/deberta-base-fine-tuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/geckos/deberta-base-fine-tuned-ner/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 85036860ef27c2d87b07afbc1d72bd17e8f2a3f6a388f65a025dc02b5b5931e7
- Size of remote file:
- 2.86 kB
- SHA256:
- 9938b4bb7359edcf4febfb91e9b03b0fd2224cb4bb5b4472a1e244f58810128d
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