Instructions to use SlayerLab/NERGAL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SlayerLab/NERGAL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SlayerLab/NERGAL")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SlayerLab/NERGAL") model = AutoModelForTokenClassification.from_pretrained("SlayerLab/NERGAL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,253 Bytes
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"full_name": "Named Entity Recognition with Grounded Additive Labels",
"hub_id": "SlayerLab/NERGAL",
"version": "1.1.2",
"mode": "rules_union",
"epoch": 5,
"seed": 202609160,
"threshold": 0.95,
"rules_sha256": "08faef844c850bcd438c904d0b3f898df47c8bde8dd827d36ebffd39dc1594fb",
"eval": {
"split": "841-dev",
"gold_amendments": [
"gold_check_v2"
],
"gold_entities": 354,
"whole_entities": 326,
"residual_passages": 23,
"union_fp": 80,
"rules_fp": 24,
"character_precision": 0.9865,
"character_recall": 0.9649,
"exact_precision": 0.8641,
"exact_recall": 0.8983,
"exact_f1": 0.8809,
"phone_whole": 147,
"phone_gold": 169,
"pii_whole": 179,
"pii_gold": 185
},
"source_checkpoint_sha256": "063ee5f9782c1b4d99e838be5a836328718e1372e213d5b87098b371b5c162af",
"model_safetensors_sha256": "1d42c34459e90cd25db44f92bb31fb2be1ef3a1b1e34c599162e1895057c08f6",
"gaps": [
"[PII_SPACE]",
"[PII_BREAK]"
],
"gap_ids": [
250002,
250003
],
"drop_in_token_classification_pipeline": false,
"promotion_authorized": false,
"backbone": {
"repo": "FacebookAI/xlm-roberta-large",
"revision": "c23d21b0620b635a76227c604d44e43a9f0ee389"
}
}
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