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suayptalha
/
Medical-Router

Text Classification
Transformers
Safetensors
English
modernbert
Mixture of Experts
text-embeddings-inference
Model card Files
xet
 Community
How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="suayptalha/Medical-Router")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("suayptalha/Medical-Router")
model = AutoModelForSequenceClassification.from_pretrained("suayptalha/Medical-Router")
Quick Links

MoE Router Model

Classify clinical text into:

  • 0: Diagnosis
  • 1: Treatment
  • 2: Psychological Support

Training

  • Base model: ModernBERT-base
  • Epochs: 3
  • Learning rate: 3e-5
  • Batch size: 16
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16
Safetensors
Model size
0.1B params
Tensor type
F32
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Model tree for suayptalha/Medical-Router

Base model

answerdotai/ModernBERT-base
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Datasets used to train suayptalha/Medical-Router