Text Classification
Transformers
Safetensors
English
proto
medical
prototypical-networks
Eval Results (legacy)
Instructions to use row56/ProtoPatient with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use row56/ProtoPatient with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="row56/ProtoPatient")# Load model directly from transformers import ProtoForMultiLabelClassification model = ProtoForMultiLabelClassification.from_pretrained("row56/ProtoPatient", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +3 -1
config.json
CHANGED
|
@@ -8,5 +8,7 @@
|
|
| 8 |
"use_sigmoid": true,
|
| 9 |
"label_order_path": "label_order.json",
|
| 10 |
"prototype_vector_path": "prototype_vectors",
|
| 11 |
-
"attention_vector_path": "attention_vectors"
|
|
|
|
|
|
|
| 12 |
}
|
|
|
|
| 8 |
"use_sigmoid": true,
|
| 9 |
"label_order_path": "label_order.json",
|
| 10 |
"prototype_vector_path": "prototype_vectors",
|
| 11 |
+
"attention_vector_path": "attention_vectors",
|
| 12 |
+
"prototype_vector_path": "model.safetensors",
|
| 13 |
+
"attention_vector_path": "model.safetensors"
|
| 14 |
}
|