Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Granoladata/contrast_classifier_biobert_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Granoladata/contrast_classifier_biobert_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Granoladata/contrast_classifier_biobert_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Granoladata/contrast_classifier_biobert_v2") model = AutoModelForSequenceClassification.from_pretrained("Granoladata/contrast_classifier_biobert_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a1ddd8bf04e5ce3a01ae21404036a3aa6fd20e0a437d462e48d79bf3138d10a
- Size of remote file:
- 4.6 kB
- SHA256:
- 4b6bb435198f6f1ebe0a15c9a1d46e1df747f632d68f919b10e3aafcf8b37b51
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