Instructions to use denizspynk/req_mod_ner_modelv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use denizspynk/req_mod_ner_modelv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="denizspynk/req_mod_ner_modelv2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("denizspynk/req_mod_ner_modelv2") model = AutoModelForTokenClassification.from_pretrained("denizspynk/req_mod_ner_modelv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 551 Bytes
c14d651 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"add_prefix_space": true,
"bos_token": "<s>",
"cls_token": "<s>",
"do_lower_case": false,
"eos_token": "</s>",
"errors": "replace",
"mask_token": "<mask>",
"name_or_path": "pdelobelle/robbert-v2-dutch-ner",
"pad_token": "<pad>",
"sep_token": "</s>",
"special_tokens_map_file": "/Users/denizayhan/.cache/huggingface/hub/models--pdelobelle--robbert-v2-dutch-ner/snapshots/cbe384104e418a84b62a102e1aa61f75857ed20e/special_tokens_map.json",
"tokenizer_class": "RobertaTokenizer",
"trim_offsets": true,
"unk_token": "<unk>"
}
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