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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b737e7296a63b514ae36924059188f0202608940d07a6b958a536f8c039ae0e
- Size of remote file:
- 598 MB
- SHA256:
- b2fb4570aecc883141263a43f8a54982c64071b164a72e4dd889934a07f83523
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