Token Classification
Transformers
PyTorch
English
deberta-v2
NER
token classification
information extraction
question answering
Instructions to use knowledgator/UTC-DeBERTA-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knowledgator/UTC-DeBERTA-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="knowledgator/UTC-DeBERTA-base")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("knowledgator/UTC-DeBERTA-base") model = AutoModelForTokenClassification.from_pretrained("knowledgator/UTC-DeBERTA-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from knowledgator/UTC-DeBERTA-base: direct link, hf CLI and curl.
- Browser
- Download file 23 Bytes
-
https://huggingface.co/knowledgator/UTC-DeBERTA-base/resolve/main/added_tokens.json
- Command line
-
hf download hf://knowledgator/UTC-DeBERTA-base/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/knowledgator/UTC-DeBERTA-base/resolve/main/added_tokens.json
23 Bytes
| { | |
| "[MASK]": 128000 | |
| } | |