Text Classification
Transformers
TensorBoard
Safetensors
English
bert
Generated from Trainer
custom_code
text-embeddings-inference
Instructions to use gyr66/relation_extraction_bert_base_uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gyr66/relation_extraction_bert_base_uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gyr66/relation_extraction_bert_base_uncased", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gyr66/relation_extraction_bert_base_uncased", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("gyr66/relation_extraction_bert_base_uncased", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update config.json
b11adb1 -
Upload BertForRelationExtraction
7483a21
-
Update README.md
477ebb5 -
End of training
5737258 -
Model save
c860a54 -
Training in progress, epoch 10
c064404 -
Training in progress, epoch 9
e2ebcbe -
Training in progress, epoch 8
1c3aee7 -
Training in progress, epoch 7
22a43c7 -
Training in progress, epoch 6
b17c4d9 -
Training in progress, epoch 5
226d592 -
Training in progress, epoch 4
4bdc682 -
Training in progress, epoch 3
184e004 -
Training in progress, epoch 2
49cba7d -
Training in progress, epoch 1
5603eec -
initial commit
8f50adc