Instructions to use dgramus/ner-best-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dgramus/ner-best-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dgramus/ner-best-model")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dgramus/ner-best-model", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| tokenizer_config.json filter=lfs diff=lfs merge=lfs -text | |
| tokenizer.json filter=lfs diff=lfs merge=lfs -text | |
| special_tokens_map.json filter=lfs diff=lfs merge=lfs -text | |
| sentencepiece.bpe.model filter=lfs diff=lfs merge=lfs -text | |
| model.safetensors filter=lfs diff=lfs merge=lfs -text | |
| config.json filter=lfs diff=lfs merge=lfs -text | |