Token Classification
Transformers
Safetensors
English
distilbert
document-understanding
procurement
india
gem
synthetic-data
Instructions to use HarshilDaGoat/gem-certificate-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HarshilDaGoat/gem-certificate-extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HarshilDaGoat/gem-certificate-extractor")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HarshilDaGoat/gem-certificate-extractor") model = AutoModelForTokenClassification.from_pretrained("HarshilDaGoat/gem-certificate-extractor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from HarshilDaGoat/gem-certificate-extractor: direct link, hf CLI and curl.
- Browser
- Download file 1.74 kB
-
https://huggingface.co/HarshilDaGoat/gem-certificate-extractor/resolve/main/config.json
- Command line
-
hf download hf://HarshilDaGoat/gem-certificate-extractor/config.json
-
curl -L -o config.json https://huggingface.co/HarshilDaGoat/gem-certificate-extractor/resolve/main/config.json
1.74 kB
| { | |
| "activation": "gelu", | |
| "architectures": [ | |
| "DistilBertForTokenClassification" | |
| ], | |
| "attention_dropout": 0.1, | |
| "bos_token_id": null, | |
| "dim": 768, | |
| "dropout": 0.1, | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "hidden_dim": 3072, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-GSTIN", | |
| "2": "I-GSTIN", | |
| "3": "B-PAN", | |
| "4": "I-PAN", | |
| "5": "B-UDYAM", | |
| "6": "I-UDYAM", | |
| "7": "B-CIN", | |
| "8": "I-CIN", | |
| "9": "B-EPFO", | |
| "10": "I-EPFO", | |
| "11": "B-DPIIT", | |
| "12": "I-DPIIT", | |
| "13": "B-TRADE_NAME", | |
| "14": "I-TRADE_NAME", | |
| "15": "B-LEGAL_NAME", | |
| "16": "I-LEGAL_NAME", | |
| "17": "B-ACTIVITY", | |
| "18": "I-ACTIVITY", | |
| "19": "B-CATEGORY", | |
| "20": "I-CATEGORY", | |
| "21": "B-LOCAL_CONTENT", | |
| "22": "I-LOCAL_CONTENT", | |
| "23": "B-VALID_UNTIL", | |
| "24": "I-VALID_UNTIL" | |
| }, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "B-ACTIVITY": 17, | |
| "B-CATEGORY": 19, | |
| "B-CIN": 7, | |
| "B-DPIIT": 11, | |
| "B-EPFO": 9, | |
| "B-GSTIN": 1, | |
| "B-LEGAL_NAME": 15, | |
| "B-LOCAL_CONTENT": 21, | |
| "B-PAN": 3, | |
| "B-TRADE_NAME": 13, | |
| "B-UDYAM": 5, | |
| "B-VALID_UNTIL": 23, | |
| "I-ACTIVITY": 18, | |
| "I-CATEGORY": 20, | |
| "I-CIN": 8, | |
| "I-DPIIT": 12, | |
| "I-EPFO": 10, | |
| "I-GSTIN": 2, | |
| "I-LEGAL_NAME": 16, | |
| "I-LOCAL_CONTENT": 22, | |
| "I-PAN": 4, | |
| "I-TRADE_NAME": 14, | |
| "I-UDYAM": 6, | |
| "I-VALID_UNTIL": 24, | |
| "O": 0 | |
| }, | |
| "max_position_embeddings": 512, | |
| "model_type": "distilbert", | |
| "n_heads": 12, | |
| "n_layers": 6, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "qa_dropout": 0.1, | |
| "seq_classif_dropout": 0.2, | |
| "sinusoidal_pos_embds": false, | |
| "tie_weights_": true, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.17.0", | |
| "use_cache": false, | |
| "vocab_size": 28996 | |
| } | |