Instructions to use mnaylor/bigbird-base-mimic-mortality with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mnaylor/bigbird-base-mimic-mortality with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mnaylor/bigbird-base-mimic-mortality")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mnaylor/bigbird-base-mimic-mortality") model = AutoModelForSequenceClassification.from_pretrained("mnaylor/bigbird-base-mimic-mortality", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add openrail license
Browse files
README.md
CHANGED
|
@@ -1,3 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
| 1 |
# BigBird for Mortality Prediction
|
| 2 |
|
| 3 |
Starting with Google's base BigBird model, we fine-tuned on binary mortality prediction in MIMIC admission notes. This
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: bigscience-openrail-m
|
| 3 |
+
---
|
| 4 |
# BigBird for Mortality Prediction
|
| 5 |
|
| 6 |
Starting with Google's base BigBird model, we fine-tuned on binary mortality prediction in MIMIC admission notes. This
|