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)# 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) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88b1466400ae320a94c05a5d3ab0a8e3c86d1f24c82af5baea6fa325a7c196ca
- Size of remote file:
- 4.6 kB
- SHA256:
- bf22ef31d302fcf6027fb7ada08120ad9d3b9afdd46089334e6f20aef07417e3
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