Instructions to use cwtpc/wangchanberta-ner-8989 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cwtpc/wangchanberta-ner-8989 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cwtpc/wangchanberta-ner-8989")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cwtpc/wangchanberta-ner-8989") model = AutoModelForTokenClassification.from_pretrained("cwtpc/wangchanberta-ner-8989", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 498 Bytes
6e773d0 | 1 | {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "additional_special_tokens": ["<s>NOTUSED", "</s>NOTUSED", "<_>"], "sp_model_kwargs": {}, "do_lower_case": false, "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "ner/", "tokenizer_class": "CamembertTokenizer"} |