Token Classification
Transformers
ONNX
Safetensors
PEFT
English
bert
ner
legal
legal-bert
nigerian-law
lora
Instructions to use WhiteRoomProdigy/amicus-ner-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WhiteRoomProdigy/amicus-ner-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="WhiteRoomProdigy/amicus-ner-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("WhiteRoomProdigy/amicus-ner-v2") model = AutoModelForTokenClassification.from_pretrained("WhiteRoomProdigy/amicus-ner-v2") - PEFT
How to use WhiteRoomProdigy/amicus-ner-v2 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
amicus-ner-v2: LoRA fine-tuned on Nigerian legal corpus (regex silver labels + Gemini augmentation)
6eba0e5 verified | { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "eos_token_ids": 0, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-CASE_NAME", | |
| "2": "I-CASE_NAME", | |
| "3": "B-CITATION", | |
| "4": "I-CITATION", | |
| "5": "B-STATUTE", | |
| "6": "I-STATUTE", | |
| "7": "B-COURT", | |
| "8": "I-COURT", | |
| "9": "B-DATE", | |
| "10": "I-DATE", | |
| "11": "B-JUDGE", | |
| "12": "I-JUDGE", | |
| "13": "B-RATIO", | |
| "14": "I-RATIO", | |
| "15": "B-HELD", | |
| "16": "I-HELD" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "B-CASE_NAME": 1, | |
| "B-CITATION": 3, | |
| "B-COURT": 7, | |
| "B-DATE": 9, | |
| "B-HELD": 15, | |
| "B-JUDGE": 11, | |
| "B-RATIO": 13, | |
| "B-STATUTE": 5, | |
| "I-CASE_NAME": 2, | |
| "I-CITATION": 4, | |
| "I-COURT": 8, | |
| "I-DATE": 10, | |
| "I-HELD": 16, | |
| "I-JUDGE": 12, | |
| "I-RATIO": 14, | |
| "I-STATUTE": 6, | |
| "O": 0 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.12.1", | |
| "type_vocab_size": 2, | |
| "use_cache": false, | |
| "vocab_size": 30522 | |
| } | |