Token Classification
Transformers
Safetensors
Arabic
bert
nested-ner
multi-label
arabic
wojood
konooz
knowledgegrapheval-2026
arabicnlp-2026
adaptner
Eval Results (legacy)
Instructions to use NAMAA-Space/KnowledgeGraphEval-2026-AdaptNER-MARBERTv2-Nested with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NAMAA-Space/KnowledgeGraphEval-2026-AdaptNER-MARBERTv2-Nested with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="NAMAA-Space/KnowledgeGraphEval-2026-AdaptNER-MARBERTv2-Nested")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("NAMAA-Space/KnowledgeGraphEval-2026-AdaptNER-MARBERTv2-Nested") model = AutoModelForTokenClassification.from_pretrained("NAMAA-Space/KnowledgeGraphEval-2026-AdaptNER-MARBERTv2-Nested", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from NAMAA-Space/KnowledgeGraphEval-2026-AdaptNER-MARBERTv2-Nested: direct link, hf CLI and curl.
- Browser
- Download file 2.65 kB
-
https://huggingface.co/NAMAA-Space/KnowledgeGraphEval-2026-AdaptNER-MARBERTv2-Nested/resolve/main/config.json
- Command line
-
hf download hf://NAMAA-Space/KnowledgeGraphEval-2026-AdaptNER-MARBERTv2-Nested/config.json
-
curl -L -o config.json https://huggingface.co/NAMAA-Space/KnowledgeGraphEval-2026-AdaptNER-MARBERTv2-Nested/resolve/main/config.json
2.65 kB
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "classifier_dropout": null, | |
| "directionality": "bidi", | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "B-CARDINAL", | |
| "1": "B-CURR", | |
| "2": "B-DATE", | |
| "3": "B-EVENT", | |
| "4": "B-FAC", | |
| "5": "B-GPE", | |
| "6": "B-LANGUAGE", | |
| "7": "B-LAW", | |
| "8": "B-LOC", | |
| "9": "B-MONEY", | |
| "10": "B-NORP", | |
| "11": "B-OCC", | |
| "12": "B-ORDINAL", | |
| "13": "B-ORG", | |
| "14": "B-PERCENT", | |
| "15": "B-PERS", | |
| "16": "B-PRODUCT", | |
| "17": "B-QUANTITY", | |
| "18": "B-TIME", | |
| "19": "B-UNIT", | |
| "20": "B-WEBSITE", | |
| "21": "I-CARDINAL", | |
| "22": "I-CURR", | |
| "23": "I-DATE", | |
| "24": "I-EVENT", | |
| "25": "I-FAC", | |
| "26": "I-GPE", | |
| "27": "I-LANGUAGE", | |
| "28": "I-LAW", | |
| "29": "I-LOC", | |
| "30": "I-MONEY", | |
| "31": "I-NORP", | |
| "32": "I-OCC", | |
| "33": "I-ORDINAL", | |
| "34": "I-ORG", | |
| "35": "I-PERCENT", | |
| "36": "I-PERS", | |
| "37": "I-PRODUCT", | |
| "38": "I-QUANTITY", | |
| "39": "I-TIME", | |
| "40": "I-UNIT", | |
| "41": "I-WEBSITE" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "label2id": { | |
| "B-CARDINAL": 0, | |
| "B-CURR": 1, | |
| "B-DATE": 2, | |
| "B-EVENT": 3, | |
| "B-FAC": 4, | |
| "B-GPE": 5, | |
| "B-LANGUAGE": 6, | |
| "B-LAW": 7, | |
| "B-LOC": 8, | |
| "B-MONEY": 9, | |
| "B-NORP": 10, | |
| "B-OCC": 11, | |
| "B-ORDINAL": 12, | |
| "B-ORG": 13, | |
| "B-PERCENT": 14, | |
| "B-PERS": 15, | |
| "B-PRODUCT": 16, | |
| "B-QUANTITY": 17, | |
| "B-TIME": 18, | |
| "B-UNIT": 19, | |
| "B-WEBSITE": 20, | |
| "I-CARDINAL": 21, | |
| "I-CURR": 22, | |
| "I-DATE": 23, | |
| "I-EVENT": 24, | |
| "I-FAC": 25, | |
| "I-GPE": 26, | |
| "I-LANGUAGE": 27, | |
| "I-LAW": 28, | |
| "I-LOC": 29, | |
| "I-MONEY": 30, | |
| "I-NORP": 31, | |
| "I-OCC": 32, | |
| "I-ORDINAL": 33, | |
| "I-ORG": 34, | |
| "I-PERCENT": 35, | |
| "I-PERS": 36, | |
| "I-PRODUCT": 37, | |
| "I-QUANTITY": 38, | |
| "I-TIME": 39, | |
| "I-UNIT": 40, | |
| "I-WEBSITE": 41 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "position_embedding_type": "absolute", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.10.2", | |
| "type_vocab_size": 2, | |
| "use_cache": false, | |
| "vocab_size": 100000 | |
| } | |