Token Classification
Transformers
Safetensors
layoutlmv3
ner
on-device
privacy
flowx
openner
cross
de-identification
Instructions to use flowxai/docformner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowxai/docformner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="flowxai/docformner")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("flowxai/docformner") model = AutoModelForTokenClassification.from_pretrained("flowxai/docformner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 654 Bytes
d58e253 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | {
"add_prefix_space": true,
"apply_ocr": false,
"backend": "tokenizers",
"bos_token": "<s>",
"cls_token": "<s>",
"cls_token_box": [
0,
0,
0,
0
],
"eos_token": "</s>",
"errors": "replace",
"is_local": false,
"local_files_only": false,
"mask_token": "<mask>",
"model_max_length": 512,
"only_label_first_subword": true,
"pad_token": "<pad>",
"pad_token_box": [
0,
0,
0,
0
],
"pad_token_label": -100,
"processor_class": "LayoutLMv3Processor",
"sep_token": "</s>",
"sep_token_box": [
0,
0,
0,
0
],
"tokenizer_class": "LayoutLMv3Tokenizer",
"unk_token": "<unk>"
}
|