Text Classification
Transformers
PyTorch
Safetensors
English
TransformerTextClassificationModel
Eval Results (legacy)
Instructions to use DFKI-SLT/relation_classification_tacred_revisited with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DFKI-SLT/relation_classification_tacred_revisited with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DFKI-SLT/relation_classification_tacred_revisited")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DFKI-SLT/relation_classification_tacred_revisited", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
datasets:
- DFKI-SLT/tacred
language:
- en
metrics:
- f1
library_name: transformers
pipeline_tag: text-classification
model-index:
- name: re_bert-base_tacred
results:
- task:
type: relation-classification
name: Relation Classification
dataset:
type: DFKI-SLT/tacred
name: TAC Relation Extraction Dataset
config: revisited
split: test
metrics:
- type: f1
value: 0.7985
name: test/f1
verified: false