Instructions to use medspaner/mdeberta-v3-base-es-trials-attributes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use medspaner/mdeberta-v3-base-es-trials-attributes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="medspaner/mdeberta-v3-base-es-trials-attributes")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("medspaner/mdeberta-v3-base-es-trials-attributes") model = AutoModelForTokenClassification.from_pretrained("medspaner/mdeberta-v3-base-es-trials-attributes") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot