Token Classification
Transformers
Safetensors
English
umt5
text2text-generation
ner
named-entity-recognition
biomedical
en-vimedner
Instructions to use nhuvo/umt5-base-en-vimedner-ner-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhuvo/umt5-base-en-vimedner-ner-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nhuvo/umt5-base-en-vimedner-ner-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nhuvo/umt5-base-en-vimedner-ner-en") model = AutoModelForSeq2SeqLM.from_pretrained("nhuvo/umt5-base-en-vimedner-ner-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!