Token Classification
Transformers
PyTorch
TensorBoard
electra
Generated from Trainer
Eval Results (legacy)
Instructions to use chintagunta85/electramed-small-deid2014-ner-v5-classweights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chintagunta85/electramed-small-deid2014-ner-v5-classweights with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chintagunta85/electramed-small-deid2014-ner-v5-classweights")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("chintagunta85/electramed-small-deid2014-ner-v5-classweights") model = AutoModelForTokenClassification.from_pretrained("chintagunta85/electramed-small-deid2014-ner-v5-classweights") - Notebooks
- Google Colab
- Kaggle
File size: 546 Bytes
277ecc0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"cls_token": "[CLS]",
"do_basic_tokenize": true,
"do_lower_case": true,
"mask_token": "[MASK]",
"name_or_path": "giacomomiolo/electramed_small_scivocab",
"never_split": null,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"special_tokens_map_file": "/root/.cache/huggingface/hub/models--giacomomiolo--electramed_small_scivocab/snapshots/d66f0eec09a066c59818c942ff2c2eecaf2718ca/special_tokens_map.json",
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "ElectraTokenizer",
"unk_token": "[UNK]"
}
|