Instructions to use seppestaes/layoutlm-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seppestaes/layoutlm-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="seppestaes/layoutlm-funsd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("seppestaes/layoutlm-funsd") model = AutoModelForTokenClassification.from_pretrained("seppestaes/layoutlm-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from seppestaes/layoutlm-funsd: direct link, hf CLI and curl.
- Browser
- Download file 652 Bytes
-
https://huggingface.co/seppestaes/layoutlm-funsd/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://seppestaes/layoutlm-funsd/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/seppestaes/layoutlm-funsd/resolve/main/tokenizer_config.json
652 Bytes
| {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "cls_token_box": [0, 0, 0, 0], "sep_token_box": [1000, 1000, 1000, 1000], "pad_token_box": [0, 0, 0, 0], "pad_token_label": -100, "only_label_first_subword": true, "tokenize_chinese_chars": true, "strip_accents": null, "apply_ocr": false, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "microsoft/layoutlmv2-base-uncased", "do_basic_tokenize": true, "never_split": null, "additional_special_tokens": null, "tokenizer_class": "LayoutLMv2Tokenizer", "processor_class": "LayoutLMv2Processor"} |