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")# pip install -U transformers accelerate # 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
Download tokenizer.json from chronologic/chronologic-date-deberta: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/chronologic/chronologic-date-deberta/resolve/main/tokenizer.json
- Command line
-
hf download hf://chronologic/chronologic-date-deberta/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/chronologic/chronologic-date-deberta/resolve/main/tokenizer.json
8.66 MB
File too large to display, you can check the raw version instead.