Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Granoladata/contrast_classifier_bio_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Granoladata/contrast_classifier_bio_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Granoladata/contrast_classifier_bio_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Granoladata/contrast_classifier_bio_bert") model = AutoModelForSequenceClassification.from_pretrained("Granoladata/contrast_classifier_bio_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3de82162038e7c7326cce7e37f6fe3b2b350ba5139d5528c746774b04a374dc9
- Size of remote file:
- 433 MB
- SHA256:
- ef4a1c144c9b5940d760c2e7d54e474bbf18ce8b5ed844e6f33673095caeee18
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