Text Classification
Transformers
Safetensors
English
bert
pharmacovigilance
drug-safety
adverse-drug-reactions
clinical-nlp
biobert
drug-causality
ade-corpus
medical-nlp
text-embeddings-inference
Instructions to use PrashantRGore/drug-causality-bert-v2-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PrashantRGore/drug-causality-bert-v2-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PrashantRGore/drug-causality-bert-v2-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PrashantRGore/drug-causality-bert-v2-model") model = AutoModelForSequenceClassification.from_pretrained("PrashantRGore/drug-causality-bert-v2-model") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
ffc774b | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:ca6a57bb3665602515473f6c3e6aa96cb5505d7b8642beb6c8604c4a00aec451
size 5777
|