Token Classification
Transformers
Safetensors
English
German
modernbert
ner
named-entity-recognition
knowledge-platform
multilingual
patents
scientific-papers
cross-domain
english
german
Generated from Trainer
Eval Results (legacy)
Instructions to use deepakint/knowledge-platform-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepakint/knowledge-platform-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="deepakint/knowledge-platform-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("deepakint/knowledge-platform-ner") model = AutoModelForTokenClassification.from_pretrained("deepakint/knowledge-platform-ner") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "[MASK]", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 8192, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "[UNK]" | |
| } | |