Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
bert
Generated from Trainer
medical
text-embeddings-inference
Instructions to use opentargets/clinical_trial_stop_reasons with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opentargets/clinical_trial_stop_reasons with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="opentargets/clinical_trial_stop_reasons")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("opentargets/clinical_trial_stop_reasons") model = AutoModelForSequenceClassification.from_pretrained("opentargets/clinical_trial_stop_reasons", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K