Text Classification
Transformers
Safetensors
English
deberta-v2
digital-humanities
historical-text
dating
deberta-v3
chronologic
Eval Results (legacy)
text-embeddings-inference
Instructions to use chronologic/chronologic-date-deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chronologic/chronologic-date-deberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chronologic/chronologic-date-deberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chronologic/chronologic-date-deberta") model = AutoModelForSequenceClassification.from_pretrained("chronologic/chronologic-date-deberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "DebertaV2ForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "date_bin_width": 10, | |
| "date_grid_hi": 2040, | |
| "date_grid_lo": 1680, | |
| "date_sigma": 15.0, | |
| "dtype": "float32", | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "1680s", | |
| "1": "1690s", | |
| "2": "1700s", | |
| "3": "1710s", | |
| "4": "1720s", | |
| "5": "1730s", | |
| "6": "1740s", | |
| "7": "1750s", | |
| "8": "1760s", | |
| "9": "1770s", | |
| "10": "1780s", | |
| "11": "1790s", | |
| "12": "1800s", | |
| "13": "1810s", | |
| "14": "1820s", | |
| "15": "1830s", | |
| "16": "1840s", | |
| "17": "1850s", | |
| "18": "1860s", | |
| "19": "1870s", | |
| "20": "1880s", | |
| "21": "1890s", | |
| "22": "1900s", | |
| "23": "1910s", | |
| "24": "1920s", | |
| "25": "1930s", | |
| "26": "1940s", | |
| "27": "1950s", | |
| "28": "1960s", | |
| "29": "1970s", | |
| "30": "1980s", | |
| "31": "1990s", | |
| "32": "2000s", | |
| "33": "2010s", | |
| "34": "2020s", | |
| "35": "2030s" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "1680s": 0, | |
| "1690s": 1, | |
| "1700s": 2, | |
| "1710s": 3, | |
| "1720s": 4, | |
| "1730s": 5, | |
| "1740s": 6, | |
| "1750s": 7, | |
| "1760s": 8, | |
| "1770s": 9, | |
| "1780s": 10, | |
| "1790s": 11, | |
| "1800s": 12, | |
| "1810s": 13, | |
| "1820s": 14, | |
| "1830s": 15, | |
| "1840s": 16, | |
| "1850s": 17, | |
| "1860s": 18, | |
| "1870s": 19, | |
| "1880s": 20, | |
| "1890s": 21, | |
| "1900s": 22, | |
| "1910s": 23, | |
| "1920s": 24, | |
| "1930s": 25, | |
| "1940s": 26, | |
| "1950s": 27, | |
| "1960s": 28, | |
| "1970s": 29, | |
| "1980s": 30, | |
| "1990s": 31, | |
| "2000s": 32, | |
| "2010s": 33, | |
| "2020s": 34, | |
| "2030s": 35 | |
| }, | |
| "layer_norm_eps": 1e-07, | |
| "legacy": true, | |
| "max_position_embeddings": 512, | |
| "max_relative_positions": -1, | |
| "model_type": "deberta-v2", | |
| "norm_rel_ebd": "layer_norm", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "pad_token_id": 0, | |
| "pooler_dropout": 0, | |
| "pooler_hidden_act": "gelu", | |
| "pooler_hidden_size": 1024, | |
| "pos_att_type": [ | |
| "p2c", | |
| "c2p" | |
| ], | |
| "position_biased_input": false, | |
| "position_buckets": 256, | |
| "relative_attention": true, | |
| "share_att_key": true, | |
| "transformers_version": "4.57.6", | |
| "type_vocab_size": 0, | |
| "vocab_size": 128100 | |
| } | |