Token Classification
Transformers
PyTorch
English
deberta-v2
NER
token classification
information extraction
question answering
Instructions to use knowledgator/UTC-DeBERTa-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knowledgator/UTC-DeBERTa-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="knowledgator/UTC-DeBERTa-large")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("knowledgator/UTC-DeBERTa-large") model = AutoModelForTokenClassification.from_pretrained("knowledgator/UTC-DeBERTa-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from knowledgator/UTC-DeBERTa-large: direct link, hf CLI and curl.
- Browser
- Download file 1.74 GB
-
https://huggingface.co/knowledgator/UTC-DeBERTa-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://knowledgator/UTC-DeBERTa-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/knowledgator/UTC-DeBERTa-large/resolve/main/pytorch_model.bin
1.74 GB
- Xet hash:
- 7b8c3e92722d25b3798c29fc870b438240275ac87e54a7e728252c755841fb6f
- Size of remote file:
- 1.74 GB
- SHA256:
- 5201cd4fdc96e19cd4aca3dddf4c92c4afb497d43434f27f3d3ccacf7582d1b6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.