Instructions to use Granoladata/modality_classifier_biobert_augmented_classes_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Granoladata/modality_classifier_biobert_augmented_classes_v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Granoladata/modality_classifier_biobert_augmented_classes_v0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Granoladata/modality_classifier_biobert_augmented_classes_v0") model = AutoModelForSequenceClassification.from_pretrained("Granoladata/modality_classifier_biobert_augmented_classes_v0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 230bc7e2a1325df1115b798fb8221c1d663ef80ef4e4b24b9041d4dedcc21d01
- Size of remote file:
- 4.98 kB
- SHA256:
- d6494a108fcbdbd019002facb88ebb2e0ed6803201ca244f9fba3d12620934ed
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.