Text Classification
Transformers
Safetensors
English
modernbert
Mixture of Experts
text-embeddings-inference
Instructions to use suayptalha/Medical-Router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suayptalha/Medical-Router with Transformers:
# 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# MoE Router Model
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Classify clinical text into:
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* **0:** Diagnosis
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* **1:** Treatment
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* **2:** Psychological Support
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## Training
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* **Base model:** ModernBERT-base
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* **Epochs:** 3
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* **Learning rate:** 3e-5
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* **Batch size:** 16
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